We propose a forearm-worn haptic device that integrates tactile skin-stretch feedback with kinaesthetic force feedback from a grounded haptic device. The wearable module generates lateral skin deformation corresponding to the tangential components of the applied kinaesthetic force, moving the skin in the opposite direction to produce coherent tactile cues that effectively convey sensations of surface friction and tangential shear, reinforcing the perception of contact with virtual surfaces. This integration aims to enhance both perceptual realism and transparency during haptic interaction. A series of preliminary experiments were conducted in a Chai3D-based virtual environment, where users interacted with virtual walls and corners while receiving combined feedback. The results demonstrate that the proposed device can render directionally accurate and temporally synchronized skin-stretch cues consistent with the kinaesthetic forces, validating its potential for multimodal haptic interaction.

Traditional dances play a crucial role in preserving cultural identity, fostering community bonds, and maintaining artistic heritage. The integration of robotics into this domain, leveraging AI, motion-capture, and mapping algorithms, introduces new possibilities for replicating traditional choreography using artificial agents. However, this fusion raises important questions about authenticity, cultural impact, and the role of technology in artistic expression.These concerns become even more relevant when the artificial agent is a non-humanoid robot, as the mapping process becomes more complex. In a previous study, we proposed a Principal Component Analysis (PCA)-based projection method to transfer human dance movements onto robotic arms. This method aims to minimize movement loss by efficiently adapting the high degrees of freedom of the human body to the constrained capabilities of a robotic manipulator. While earlier research confirmed the method’s ability to produce robot movements consistent with human references, this study further explores its impact on preserving dance style identity.To evaluate this, we perform a two-phase numerical analysis. First, we investigate whether the method retains stylistic differences between movements and how it influences them. If a reduction in stylistic distinctions is observed, we proceed to examine the statistical uniqueness of the robot-generated trajectories by comparing them to human movements from both the same and different dance styles. This deeper analysis provides insights into whether the proposed mapping method maintains the essence of stylistic identity despite the transformation from human motion to robotic execution.

This article presents the results of an interdisciplinary study encompassing data collected from 108 in-depth interviews and 15 participatory workshops aimed at exploring the requirements of a diverse range of stakeholders in relation to assistive augmentative technologies. The study involved 39 post-stroke patients with hand paresis, 39 individuals with spinal cord injuries affecting upper limb function, 38 relatives and 65 healthcare professionals. Through qualitative analysis of the accumulated data, this research identified the multifaceted needs, preferences and aspirations of the study participants. We propose a structured hierarchy for user requirements, inspired by Maslow's hierarchy of needs. At the foundation of this pyramid are the essential functional requirements, forming the bedrock for the subsequent layers. Moving hierarchically, we identified reliability and security requirements, followed by usability and user experience considerations, recognition requirements and, finally, personal growth and self-fulfilment criteria. The foundational functional requirements must be fulfilled before other aspects can take precedence, creating a systematic approach to address the diverse needs of individuals with upper limb disabilities. The pyramid of requirements identified may significantly contribute to the scholarly community and lay the foundation for the development of assistive robotics that align with the desires of individuals with upper limb disabilities.

Redundant robots have the potential to perform internal joints motion without modifying the pose of the end-effector by exploiting the null-space of the Jacobian matrix. Capitalizing on that feature, we developed a control technique for minimizing the robot visual appearance when observed from an eye-to-hand camera. Such algorithm is instrumental in contexts where quickly adjusting the perspective to see objects obstructed by the robot is impractical (e.g., teleoperation in narrow environment). Diminished reality techniques are frequently employed in these cases to mitigate the robot intrusion into the environment, although these techniques may sometimes compromise the perceived realism. The experimental evaluation confirmed the effectiveness of our control algorithm, demonstrating an average reduction of 4.67% of the area covered by the robot within the frame when compared to the case without the optimization action.

Food handling is a challenging task for robotic grippers, as it requires to manipulate highly deformable and fragile items, that can be easily damaged. Moreover, ingredients for the preparation of the different dishes are usually stored in small containers that are often not easily accessible. This paper introduces an innovative soft-rigid, tendon-driven gripper: the Double-Scoop Gripper (DSG). Its two-fingered design exploits a specialized structure to cope with constrained spaces (e.g., containers in narrow shelves). The DSG can delicately grasp objects of various shapes by employing two scoop-shaped fingertips that can form a single plate when fingers are flexed. Data obtained from an on-board camera are used to detect the food item features and plan the grasping strategy that better exploits the possible environmental constraints regulating the opening of the two fingers and the approaching direction of the gripper. DSG capabilities are verified with experiments conducted using real food ingredients within a pick-and-place setup to evaluate both the grasping and the releasing capability of the gripper. Obtained results are promising and suggest that this approach could be particularly advantageous in the context of automated food serving.

The teleoperation of complex, kinematically redundant robots with loco-manipulation capabilities represents a challenge for human operators, who have to learn how to operate the many degrees of freedom of the robot to accomplish a desired task. In this context, developing an easy-to-learn and easy-to-use human-robot interface is paramount. Recent works introduced a novel teleoperation concept, which relies on a virtual physical interaction interface between the human operator and the remote robot equivalent to a "Marionette" control, but whose feedback was limited to only visual feedback on the human side. In this paper, we propose extending the "Marionette" interface by adding a wearable haptic interface to cope with the limitations given by the previous works. Leveraging the additional haptic feedback modality, the human operator gains full sensorimotor control over the robot, and the awareness about the robot’s response and interactions with the environment is greatly improved. We evaluated the proposed interface and the related teleoperation framework with naive users, assessing the teleoperation performance and the user experience with and without haptic feedback. The conducted experiments consisted in a loco-manipulation mission with the CENTAURO robot, a hybrid leg-wheel quadruped with a humanoid dual-arm upper body.

Multi-robot systems have gained increasing interest across various fields such as medicine, environmental monitoring, and more. Despite the evident advantages, the coordination of the swarm arises significant challenges for human operators, particularly concerning the cognitive burden needed for efficiently controlling the robots. In this study, we present a novel approach for enabling a human operator to effectively control the motion of multiple robots. Leveraging a shared control data-driven approach, we enable a single user to control the 9 degrees of freedom related to the pose and shape of a swarm. Our methodology was evaluated through an experimental campaign conducted in simulated 3D environments featuring a narrow cylindrical path, which could represent, e.g., blood vessels, industrial pipes. Subjective measures of cognitive load were assessed using a post-experiment questionnaire, comparing different levels of autonomy of the system. Results show substantial reductions in operator cognitive load when compared to conventional teleoperation techniques, accompanied by enhancements in task performance, including reduced completion times and fewer instances of contact with obstacles. This research underscores the efficacy of our approach in enhancing human-robot interaction and improving operational efficiency in multi-robot systems.

Cutaneous haptic feedback has recently received great attention from researchers in the robotic teleoperation field, as it has been proven to convey rich information to the human operator while guaranteeing the safety and stability of the control loop. In fact, delivering ungrounded cutaneous cues keeps the teleoperation system stable even in the presence of time-varying destabilizing factors such as hard contacts or communication delays. This aspect is particularly relevant for all the applications and scenarios where the safety of the system is of paramount importance, as in medical robotics. This article presents an overview on cutaneous haptic interaction followed by a review of the literature on cutaneous/tactile feedback systems for robotic teleoperation, categorizing the considered systems according to the type of cutaneous stimuli they can provide to the human operator. This article ends with a discussion on the role of cutaneous haptics in robotics and the perspectives of the field.

Supernumerary robotic limbs (SRLs) gained increasing interest in the last years for their applicability as healthcare and assistive technologies. These devices can either support or augment human sensorimotor capabilities, allowing users to complete tasks that are more complex than those feasible for their natural limbs. However, for a successful coordination between natural and artificial limbs, intuitiveness of interaction and perception of autonomy are key enabling features, especially for people suffering from motor disorders and impairments. The development of suitable human-robot interfaces is thus fundamental to foster the adoption of SRLs. With this work, we describe how to control an extra degree of freedom by taking advantage of what we defined the Intrinsic Kinematic Null Space, i.e. the redundancy of the human kinematic chain involved in the ongoing task. Obtained results demonstrated that the proposed control strategy is effective for performing complex tasks with a supernumerary robotic finger, and that practice improves users' control ability.

Underactuated tendon-driven fingers are a simple, yet effective solution, for realizing robotic grippers and hands. The lack of controllable degrees of actuation and precise sensing is compensated by the deformable structure of the finger, which is able to adapt to the objects to be grasped and manipulated, and also to implement grasping strategies based on environmental constraint exploitation. One of the main drawbacks of these robotic fingers is that, due to the limited number of actuators, they can only realize a limited number of movements. Finger closure motion realized by activating the tendon depends on finger mechanical properties, and in particular on elastic joint stiffness. In this paper, we introduce a passive elastic joint to be implemented in monolithic fingers in which the stiffness can be actively regulated by applying a pre-compression to the structure, controlled by a twisted-string actuator (TSA). The paper describes the working principle of the joint, investigates the relationship between pre-compression and flexural stiffness, and finally shows its application to a robotic finger composed of three phalanges.

Metaverse is an immersive shared space that remote users can access through virtual and augmented reality interfaces, enabling their avatars to interact with each other and the surrounding. Although digital objects can be manipulated, physical objects cannot be touched, grasped, or moved within the metaverse due to the lack of a suitable interface. This work proposes a solution to overcome this limitation by introducing the concept of a Physical Metaverse enabled by a new interface named “Avatarm”. The Avatarm consists in an avatar enhanced with a robotic arm that performs physical manipulation tasks while remaining entirely hidden in the metaverse. The users have the illusion that the avatar is directly manipulating objects without the mediation by a robot. The Avatarm is the first step towards a new metaverse, the “Physical Metaverse,” where users can physically interact each other and with the environment.

Augmented reality (AR) is considered one of the most promising solutions for safer procedures in several surgical specialities. Fusing patient-specific pre-operative information, typically 3D models extracted from CT scans or MRI, with real-time surgical images allows the surgeon to have detailed information on the anatomical structure of the surgical target intra-operatively. The coupling of AR and Robotics represents the next step towards introducing awareness into the surgical room, thus enhancing the surgeon's perceptual, cognitive and manipulative capabilities. This paper presents a novel integrated system for real-time AR navigation in robotic minimally invasive surgery (RMIS), composed of a robotic endoscopic camera, a robotic teleoperation implementing a software-based Remote Center of Motion (RCM), and an AR navigation software based on an initial manual registration of virtual 3D models with the real anatomy. The integrated system, as well as the individual modules, were evaluated in simulated surgical-like setups for accuracy and repeatability. The proposed system can perform high-precision tasks (position accuracy around$1 mm$and AR error lower than 7%), showing potential for application in different surgical procedures and setting the basis for autonomous robotic surgery operations.

In this paper, we present a methodology to design soft-rigid grippers able to perform different manipulation tasks. The main idea is the introduction of wave-shaped hinges whose geometrical parameters can be designed to achieve different three-dimensional impedance characteristics. This allows one to use the same tendon-driven actuation to perform different tasks including grasping objects with different shapes and in-hand manipulation of small objects. We report all design procedures and an experimental evaluation of two different prototypes exploiting two possible tasks, the first one is designed to grasp objects adapting to different shapes and dimensions, the second one performs an in-hand manipulation task consisting in object rotation with respect to an axis perpendicular to hand palm, resembling a “screw” movement. Obtained results confirm the feasibility and potentialities of the proposed methodology, that can be applied to obtain 3D printed monolithic fingers able to move in predefined directions when activated through a tendon-driven system, paving the way toward a new task-specific realization of compliant grippers.

Nowadays, especially with the Covid-19 pandemic, researchers are focusing their attention on the remote delivery of devices designed for rehabilitation purposes, allowing people to recover without the physical presence of a doctor. Manual therapy is a physical treatment that is used by therapists for the treatment of musculoskeletal pain and/or disabilities. The aim of this work is to present HAPP, a new haptic portable device, designed to help patients suffering of different patholohgies, as for instance the Complex Regional Pain Syndrome type-I disease, and more in general to investigate the effects of manual therapy for diseases of the carpus and metacarpus, by mimicking traditional mechanical and rhythmic stimuli characteristics of manual treatments. Its structure consists of a plate oriented by revolute-prismatic-spherical joints, with a rack-pinion mechanism that actuates the end-effector, stimulating the user’s hand palm. We provide details about the device, such as the mechanical design, the mathematical model and a graphical user interface. Preliminary studies in order to evaluate the device force exerted at the user’s palm were carried out.

Supernumerary Robotic Limbs (SRL) represent a new class of wearable robots that can augment human manipulation capabilities. SRL can be controlled through input interfaces worn on the user body and can interact with the environment. Such interaction can be measured and feedback to the human wearer through wearable haptic interfaces. However, human somatotopic arrangement on the central nervous system lacks a location for artificially added limbs. Where is the best location for feedback coming from a robot not directly associated with a part of the wearer’s body?This paper sheds light on the problem of the best body location for the feedback coming from an SRL as well as on the relation between the position of the input interface and the haptic interface. We have tested four different body locations - shoulder, wrist, hip, and ankle - for vibrotactile feedback coming from the simulated interaction with a robotic extra limb activated using an interface consisting of an accelerometer worn on the user’s shoulder. Results from the experiment involving 14 participants demonstrated that the ankle feedback position led to significantly worse performances when having inputs from the shoulder, whereas the other three locations led to comparable results.

Finding effective grasp strategies constitutes one of the main challenges in robotic manipulation, especially when dealing with soft, underactuated, and non-anthropomorphic hands. This work presents a Learning from Demonstration approach to extract grasp primitives using a novel reconfigurable soft hand, the Soft ScoopGripper (SSG). Starting from human demonstrations, we derived Gaussian models through which we were able to devise different grasping strategies, exploiting the SSG features. As the grasping strategies are tightly related to the characteristics of the object to be grasped, we tested two different ways of modeling objects in the training dataset and we comparatively evaluated the resulting primitives. Experimental grasping trials on unknown test objects confirmed the effectiveness of the learned primitives and showed how assuming different levels of knowledge about the object representation in the training phase influences the grasp success.

Robotic devices for rehabilitation and training is a promising and challenging research topic with a potentially huge social impact. The availability of tools for autonomously performing physiotherapy exercises increases their efficiency, provides supplementary information about results and progress, reduces physiotherapists’ efforts and the need of their physical presence during exercise sessions, and encourages autonomy and independence in people with disabilities. Nevertheless, supportive technologies developed without the inputs and feedback of the end-user throughout the design process are less likely to be adopted for their intended purpose and use case. In this article, we propose a modular hand/wrist exoskeleton that actuates the wrist flexion/extension and adduction/abduction motions and hand fingers flexion/extension motions. It is designed to be wearable and easy to control and manage and can be used by the patient in collaboration with the physiotherapist or autonomously. A user-centered design perspective has been employed in all the design and development phases. This article introduces the main features of the device and presents some tests conducted with a user having limited hand and wrist mobility.

Avoiding face-touches has been one of the most common medical recommendations since the beginning of the COVID-19 pandemic. This work aims at providing people with help in contrasting this widespread, yet noxious habit. The solution we present exploits wearable devices to detect hand motions ending up into a face-touch and promptly notify the user exploiting haptic feedback. To this aim, we propose a recurrent neural network taking as input temporal sequences of accelerometer data acquired by a smartwatch worn by the user. The trained RNN (NFT_RNN) achieves good generalization capabilities to data coming from different users, besides a lower false detections rate with respect to a rule-based detection algorithm. The suggested solution is ready-to-use and large-scale deployable, being portable on smartwatches, fitness bands and DIY devices.

The Fin-Ray principle, inspired by the physiology of fish rays, represents the foundation of a large number of robotic devices. However, despite their popularity, there is not anyad-hoctheoretical model technique for the analysis of this family of fingers. This lack is the main motivation of the presented work, which provides the mathematical modeling, analysis, and prototyping of a closed-chain Fin-Ray finger. In this scenario, the contribution of this article is twofold. At one end, we provide a general discrete Cosserat approach for the modeling of closed-chain soft robots which shares the geometrical structure of the rigid robotics counterpart. On the other end, the approach is employed to explore the family of Fin-Ray effect fingers. Finally, an improved design, which is able to conform to contacting surfaces, while maintaining stiffness out of its grasping plane, is fabricated and its performances are compared to those of a previously proposed prototype.

Robot rehabilitation is an emerging and promising topic that incorporates robotics with neuroscience and rehabilitation to define new methods for supporting patients with neurological diseases. As a consequence, the rehabilitation process could increase the efficacy exploiting the potentialities of robot-mediated therapies. Nevertheless, nowadays clinical effectiveness is not enough to widely introduce robotic technologies in such social contexts. In this paper we propose a step further, presenting an innovative exoskeleton for wrist flexion/extension and adduction/abduction motion training. It is designed to be wearable and easy to control and manage. It can be used by the patient in collaboration with the therapist or autonomously. The paper introduces the main steps of device design and development and presents some tests conducted with an user with limited wrist mobility.

One of the key advantages of robots is the high speeds at which they can operate. In industrial settings, increased velocities can lead to higher throughputs and improved efficiency. Some manipulation tasks might require the robot to perform highly dynamic operations such as shaking, or swinging while grasping an object. These fast movements may produce high accelerations and thus give rise to inertial forces that can cause a grasped object to slip. In this paper a method is proposed to determine the inertial forces that arise on a grasped object during a trajectory, find the instances at which the object might slip, and avoid these slippages by changing the trajectory, namely the orientation of the object. To exemplify the usage of this approach, two grasping tasks are realised: a prehensile and a non-prehensile grasp, and strategies to successfully perform these tasks without changing the overall duration of the trajectory are defined and evaluated.

Tactile sensation contributes to sensory-motor control and facilitates skillful manipulation of objects. If the tactile sensation can be shared between two partners, the state of each partner can be partially observed by the other, and the possibilities for cooperative work may be expanded. Recently, examples of utilizing tactile sensation in human-robot cooperative work have been proposed. For cooperative work between people, it is necessary to investigate the basic ability of humans to identify other person's motions and operations by tactile presentation. To avoid hindering work performed with the hands and fingertips, the sensation must be presented elsewhere. This study investigates the possibility of identifying other person's tool operations by presenting tactile information induced on his/her finger with a wearable vibrator on the arm. A wearable skin vibration sensor was employed to acquire tactile information during an experiment in which five different tool operations were tested. This sensor measures skin vibration while directly touching the target. We proposed a non-linear signal processing function to adjust the intensity of the skin vibration to within the range of human sensitivity for tactile presentation. We compared vibrotactile stimulation between the non-linear and linear corrections, and then conducted experiments on identifying operations. The results showed that the non-linear correction increased small signals and enhanced the variance of large signals, and that operations were significantly identified by tactile presentation to the arm.

We present the design of a highly wearable exoskeleton of hand fingers that can be used for rehabilitation applications. One of the main challenges in the design of this type of device is to reduce as much as possible the encumbrance and weight, and at the same time to guarantee performance suitable to provide a realistic and reliable motion to the user. In the proposed solution each finger is actuated by means of a single motor, and finger joint rotations are coupled to produce a natural and intuitive movement of the finger, for this reason, we exploited the concept of postural synergies. The paper presents the main design steps, the criteria adopted to choose the mechanical structure of the exoskeleton, and the features of its prototype. Compared to other solutions present in the literature, the device presented in this paper has limited weight (40 g per finger) with an interesting level of performance in terms of force (15 N).

The design of robotic grippers requires the accomplishment of several contrasting requirements. Research in under actuated soft hands is a lively topic, with several potentialities and challenges. Soft hands are simple, robust and able of adapting to uncertain environment and operative conditions, however their intrinsic compliance and underactuation reduce control capabilities and precision. Recent studies attempted to compensate this limitation by wisely exploiting environmental constraints and considering them as supports to accomplish the task rather than obstacle to avoid. The development of grasp primitives taking into account environment features leaded to interesting and encouraging results. In this paper, we propose to embed on the hand the positive aspects of studies on environmental constraints exploitation. We present a modular under actuated soft hand in which we added a scoop as a feature of the palm, which simplify object grasping. The scoop allows to grasp objects in narrow spaces, augments the possible contact areas, allows to obtain more robust grasps, with lower forces. The paper illustrates the main design principles, a prototype and experimental results.

As robotic systems become more flexible and intelligent, they must be able to move into environments with a high degree of uncertainty or clutter, such as our homes, workplaces, and the outdoors. In these unstructured scenarios, it is possible that the body of the robot collides with its surroundings. As such, it would be desirable to characterise these contacts in terms of their location and interaction forces. This paper addresses the problem of detecting and isolating collisions between a robotic manipulator and its environment, using only on-board joint torque and position sensing. The algorithm is based on a particle filter and, under some assumptions, is able to identify the contact location anywhere on the robot body. It requires the robot to perform small exploratory movements, progressively integrating the new sensing information through a Bayesian framework. The approach was tested and benchmarked in simulation, with respect to its accuracy and robustness. Validation using a robot with joint torque sensing in a real environment demonstrated the applicability of the method to real-world scenarios.

Teleoperation of multi-robot systems, e.g. dual manipulators, in cooperative manipulation tasks requires haptic feedback of multi-contact interaction forces. Classical haptic devices restrict the workspace of the human operator and provide only one contact point. An alternative solution is to enable the operator to command the robot system via free-hand motions which extends the workspace of the human. In such a setting, a multi-contact haptic feedback may be provided to the human through multiple wearable haptic devices, e.g. fingertip devices that display forces on the human fingertips. In this paper we evaluate the benefit of using wearable haptic fingertip devices to interact with a bimanual robot setup in a pick-and-place manipulation task. We show that haptic feedback through wearable devices improves task performance compared to the base condition of no haptic feedback. Therefore, wearable haptic devices are a promising interface for guidance of multi-robot manipulation systems.

In the context of robotic manipulation and grasping, the shift from a view that is static (force closure of a single posture) and contact-deprived (only contact for force closure is allowed, everything else is obstacle) towards a view that is dynamic and contact-rich (soft manipulation) has led to an increased interest in soft hands. These hands can easily exploit environmental constraints and object surfaces without risk, and safely interact with humans, but present also some challenges. Designing them is difficult, as well as predicting, modelling, and “programming” their interactions with the objects and the environment. This paper tackles the problem of simulating them in a fast and effective way, leveraging on novel and existing simulation technologies. We present a triple-layered simulation framework where dynamic properties such as stiffness are determined from slow but accurate FEM simulation data once, and then condensed into a lumped parameter model that can be used to fast simulate soft fingers and soft hands. We apply our approach to the simulation of soft pneumatic fingers.

Robots have replaced people in many manufacturing production lines but the information they gather from sensors might not be sufficient to autonomously accomplish dexterous manipulation operations. Symbiotic human-robot cooperation appears to be a more realistic near future in industrial scenarios. In this paper we present a configuration of human-robot collaboration in which the robot is sensory-augmented by means of a set of tactile signals coming from the human operator. The incorporation of low-level robot “intelligence” permits the cooperative manipulation of an object while enabling the human operator to stay focused on task itself and carry it out in the most natural way. The effectiveness of this approach is demonstrated in a use case in which a robot helps a human operator to successfully accomplish a writing task. System performance has been evaluated, considering several positions of the tiny vibration sensor in charge of gathering the human perception, by testing it on both the human hand and the co-manipulated object. Results suggest that the sensor provides valuable information for recognizing operator actions when it is placed either on the human hand or on the co-manipulated object. However, the sensor on the finger directly represents the operator's perception, while the output of the sensor attached to the object changes according to the distance between the interaction point and the sensor itself. In addition, in wearing the sensor, neither the object nor the robot need to be instrumented: the operator is free to interact with a large set of objects and collaborate with any existing robot without requiring supplemental equipment.

This paper presents a novel optimization-based passivity control algorithm for haptic-enabled bilateral teleoperation systems involving multiple degrees of freedom. In particular, in the context of energy-bounding control, the contribution focuses on the implementation of a passivity layer for an existing time-domain scheme, ensuring optimal transparency of the interaction along subsets of the environment space which are preponderant for the given task, while preserving the energy bounds required for passivity. The involved optimization problem is convex and amenable to real-time implementation. The effectiveness of the proposed design is validated via an experiment performed on a virtual teleoperated environment.

In this paper, we introduce a set of guidelines for the design of grippers suitable for a safe human robot/interaction in cooperative tasks. Modularity, adaptability, robustness, intuitive control, limited weight are some of the key elements that could allow to effectively spread these devices in industrial and service applications. Following such guidelines, we present the prototype of the Co-Gripper: a robotic device for cooperative manipulation tasks with humans. The gripper is composed of two pairs of fingers, actuated with two motors, that can be controlled in a coordinated way or independently. Each finger has a modular underactuated structure, composed of three phalanges connected by passive joints. The gripper is wireless, so it can be easily connected both to the robotic arms and on passive structures. We designed a wearable wireless control interface composed of a ring and a bracelet allowing a simple and intuitive activation of the gripper without limiting human operator's manipulation capabilities. We performed a set of tests to quantify gripper performance and to exploit its potentialities in human-robot cooperation tasks.

Haptic systems have only recently started to be designed with wearability in mind. Compact, unobtrusive, inexpensive, easy-to-wear, and lightweight haptic devices enable researchers to provide compelling touch sensations to multiple parts of the body, significantly increasing the applicability of haptics in many fields, such as robotics, rehabilitation, gaming, and immersive systems. In this respect, wearable haptics has a great potential in the fields of virtual and augmented reality. Being able to touch virtual objects in a wearable and unobtrusive way may indeed open new exciting avenues for the fields of haptics and VR. This work presents a novel wearable haptic system for immersive virtual reality experiences. It conveys the sensation of touching objects made of different materials, rendering pressure and texture stimuli through a moving platform and a vibrotactile abbrv-doi-hyperref-narrowmotor. The device is composed of two platforms: one placed on the nail side of the finger and one in contact with the finger pad, connected by three cables. One small servomotor controls the length of the cables, moving the platform towards or away from the fingertip. One voice coil actuator, embedded in the platform, provides vibrotactile stimuli to the user.

Untethered miniature robotics have recently shown promising results in several scenarios at the microscale, such as targeted drug delivery, microassembly, and biopsy procedures. However, the vast majority of these small-scale robots have very limited manipulation capabilities, and none of the steering systems currently available enables humans to intuitively and effectively control dexterous miniaturized robots in a remote environment. In this paper, we present an innovative micro-teleoperation system with haptic assistance for the intuitive steering and control of miniaturized self-folding soft magnetic grippers in 2-D space. The soft grippers can be wirelessly positioned using weak magnetic fields and opened/closed by changing their temperature. An image-guided algorithm tracks the position of the controlled miniaturized gripper in the remote environment. A haptic interface provides the human operator with compelling haptic sensations about the interaction between the gripper and the environment as well as enables the operator to intuitively control the target position and grasping configuration of the gripper. Finally, magnetic and thermal control systems regulate the position and grasping configuration of the gripper. The viability of the proposed approach is demonstrated through two experiments involving 26 human subjects. Providing haptic stimuli elicited statistically significant improvements in the performance of the considered navigation and micro-manipulation tasks.

In this work, we propose a method to compute the stiffness of flexible joints and its realization in order to let the fingers track a certain predefined trajectory. We refer to tendon-driven, underactuated and passively compliant hands composed of deformable joints and rigid links. Specific stiffness and pre-form shapes can be assigned to the finger joints can be given s such that a single-cable actuation can be used. We firstly define a procedure to determine suitable joints stiffness and then we propose a possible realization of soft joints using rapid prototyping techniques. The stiffness computation is obtained leveraging on the the mechanics of tendon-driven hands and on compliant systems, while for its implementation beam theory has been exploited. We validate the proposed framework both in simulation and with experiments using the robotic Soft-SixthFinger, a wearable robot for grasping compensation in patients with a paretic hand, as a case study. The proposed framework can be used to design the stiffness of the passive joints in several model of underactuated tendon-driven soft hands so to improve their grasping capabilities.

In this paper we lay the foundation of the first heterogeneous multi-robot system of the Multiple Aerial-Ground Manipulator System (MAGMaS) type. A MAGMaS consists of a ground manipulator and a team of aerial robots equipped with a simple gripper manipulator the same object. The idea is to benefit from the advantages of both kinds of platforms, i.e., physical strength versus large workspace. The dynamic model of such robotic systems is derived, and its characteristic structure exhibited. Based on the dynamical structure of the system a nonlinear control scheme, augmented with a disturbance observer is proposed to perform trajectory tracking tasks in presence of model inaccuracies and external disturbances. The system redundancy is exploited by solving an optimal force/torque allocation problem that takes into account the heterogeneous system constraints and maximizes the force manipulability ellipsoid. Simulation results validated the proposed control scheme for this novel heterogeneous robotic system. We finally present a prototypical mechanical design and preliminary experimental evaluation of a MAGMaS composed by a kuka LWR4 and quadrotor based aerial robot.

Robotic teleoperation in cluttered environments is attracting increasing attention for its potential in hazardous scenarios, disaster response, and telemaintenance. Although haptic feedback has been proven effective in such applications, commercially-available grounded haptic interfaces still show significant limitations in terms of workspace, safety, transparency, and encumbrance. For this reason, we present a novel robotic teleoperation system with wearable haptic feedback for telemanipulation in cluttered environments. The slave system is composed of a soft robotic hand attached to a 6-axis force sensor, which is fixed to a 6-degrees-of-freedom robotic arm. The master system is composed of two wearable vibrotactile armbands and a Leap Motion. The armbands are worn on the upper arm and forearm, and convey information about collisions on the robotic arm and hand, respectively. The position of the manipulator and the grasping configuration of the robotic hand are controlled by the user's hand pose as tracked by the Leap Motion. To validate our approach, we carried out a human-subject telemanipulation experiment in a cluttered scenario. Twelve participants were asked to teleoperate the robot to grasp an object hidden between debris of various shapes and stiffnesses. Haptic feedback provided by our wearable devices significantly improved the performance of the considered telemanipulation tasks. All subjects but one preferred conditions with wearable haptic feedback.

Robot teams require planning and adaptive capabilities in order to perform cooperative manipulation tasks in dynamic or unstructured environments. Since these capabilities are inherent to humans, it is suitable to consider human-robot team teleoperation for cooperative manipulation where a single human collaborates with the robot team. In this paper, we present a subtask-based control approach which enables a simultaneous execution of two subtasks by the robot team, interacting with the object: trajectory tracking and formation preservation. Control inputs for both subtasks are provided by the human operator. The commands are projected onto the spaces of subtasks using a command mapping strategy. Analogously, measured interacting forces are projected onto the space of feedback signals, provided to the human via wearable fingertip haptic devices through a feedback mapping strategy. Experimental results validate the proposed approach.

We present Hand in Air Tapping (HAT), a wearable input interface which allows interactions through fingers tapping. It consists in a Bluetooth Low Energy rings enabling wireless communication with any compatible device. Each ring is hardware-wise independent of the others. This allows full modularity, i.e., the number of employed devices can be chosen to meet each application requirements. The proposed system was evaluated in two user studies, both on text input: (1) users learning curve in terms of writing speed; (2) rate of text entry comparison between the proposed interface and that of numpad style keyboards. We associated each keystroke to a set of letters/symbols and compared two approaches: one based on T9 technique and the other on multi-tap input method. Results show comparable performance between HAT and numpad style keyboards. HAT keeps the hands free, not affecting hand movements and human interactions with the surroundings. Moreover, as a general input technology, it might have several potential applications in the field of computer-human interfaces.

The human hand represents a complex fascinating system with highly sensitive sensory capabilities and dexterous grasping and manipulation functionalities. As a consequence, estimating the hand pose and at the same time having the capability to provide haptic feedback in a wearable way may benefit areas such as rehabilitation, human-robot interaction, gaming, and many more. Existing solutions allow us to accurately measure the hand configuration and provide effective force feedback to the user. However, they have limited wearability/portability. In this paper, we present the wearable sensing/actuation system glove for enhanced sensing and touching (GESTO). It is based on inertial and magnetic sensors for hand tracking, coupled with cutaneous devices for the force feedback rendering. Unlike vision-based tracking systems, the sensing glove does not suffer from occlusion problems and lighting conditions. We properly designed the cutaneous devices in order to reduce possible interferences with the magnetic sensors and performed an experimental validation on ten healthy subjects. In order to measure the estimation accuracy of GESTO, we used a high-precision optical tracker. A comparison between using the glove with and without the haptic devices shows that the presence of them does not induce a statistically significant increase in the estimation error. Experimental results revealed the effectiveness of the proposed approach. The accuracy of our system, 3.32° mean estimation error in the worst case, is comparable with the human ability of discriminating finger joint angle.

In this paper, we present a novel cooperative navigation control for human-robot teams. Assuming that a human wants to reach a final location in a large environment with the help of a mobile robot, the robot must steer the human from the initial to the target position. The challenges posed by cooperative human-robot navigation are typically addressed by using haptic feedback via physical interaction. In contrast with that, in this paper, we describe a different approach, in which the human-robot interaction is achieved via wearable vibrotactile armbands. In the proposed work, the subject is free to decide her/his own pace. A warning vibrational signal is generated by the haptic armbands when a large deviation with respect to the desired pose is detected by the robot. The proposed method has been evaluated in a large indoor environment, where 15 blindfolded human subjects were asked to follow the haptic cues provided by the robot. The participants had to reach a target area, while avoiding static and dynamic obstacles. Experimental results revealed that the blindfolded subjects were able to avoid the obstacles and safely reach the target in all of the performed trials. A comparison is provided between the results obtained with blindfolded users and experiments performed with sighted people.

Bilateral telemanipulation refers to frameworks in which a human operator manipulates a master robotic interface and a slave robotic device emulates the behavior of the master, while haptic feedback is provided to the operator. For multi-contact bilateral teleoperation wc intend master and slave systems that can establish multiple contact points with the user and with the environment. A paradigmatic example can be a multi-lingered robotic hand teleoperated by the human hand. Two of the most critical issues in this context are: (i) how to provide haptic feedback on multiple points of the human hand; (ii) how to solve the correspondence problem between the human hand and the robotic slave device. In this work, we propose finger-worn devices able to apply a three dimensional vector of force at a specific contact point to solve the multicontact feedback problem. For the correspondence problem, we propose an object-based mapping procedure. The approach is based on two virtual objects, defined both at the master and slave sides, to capture the human hand motion and to compute the related force feedback. The proposed approach has been tested in a telemanipulation framework where the master side was composed of a Leap Motion sensor used to track the hand plus three wearable haptic devices, while a robotic hand/arm system performed a manipulation task as slave.

In this paper, we propose a bilateral tele-operation scheme for cooperative aerial manipulation in which a human operator drives a team of Vertical Take-Off and Landing (VTOL) aerial vehicles, that grasped an object beforehand, and receives a force feedback depending on the states of the system. For application scenarios in which dexterous manipulation by each robot is not necessary, we propose using a rigid tool attached to the vehicle through a passive spherical joint, equipped with a simple adhesive mechanism at the tool-tip that can stick to the grasped object. Having more than two robots, we use the extra degrees of freedom to find the optimal force allocation in term of minimum power and forces smoothness. The human operator commands a desired trajectory for the robot team through a haptic interface to a pose controller, and the output of the pose controller along with system constraints, e.g., VTOL limited forces and contact maintenance, defines the feasible set of forces. Then, an on-line optimization allocates forces by minimizing a cost function of forces and their variation. Finally, propeller thrusts are computed by a dedicated attitude and thrust controller in a decentralized fashion. Human/Hardware in the loop simulation study shows efficiency of the proposed scheme, and the importance of haptic feedback to achieve a better performance.

Underactuated and synergy-driven hands are gaining attention in the grasping community mainly due to their simple kinematics, intrinsic compliance and versatility for grasping objects even in non structured scenarios. The evaluation of the grasping capabilities of such hands is a challenging task. This paper revisits some traditional quality measures developed for multi-fingered, fully actuated hands, and applies them to the case of underactuated hands. The extension of quality metrics for synergy-driven hands for the case of underactuated grasping is also presented. The performance of both types of measures is evaluated with simulated examples, concluding with a comparative discussion of their main features.

Human-Robot teams can efficiently operate in several scenarios including Urban Search and Rescue (USAR). Robots can access areas too small or deep for a person, can begin surveying larger areas that people are not permitted to enter and can carry sensors and instruments. One important aspect in this cooperative framework is the way robots and humans can communicate during rescue operation. Vision and audio modalities may result not efficient in case of reduced visibility or high noise. A promising way to guarantee effective communications between robot and human in a team is the exploitation of haptic signals. In this work, we present a possible solution to let a robot guide the position of a human operator's hand by using vibrations. We demonstrate that an armband embedding four vibrating motors is enough to guide the wrist of an operator along a predefined path or in a target location. The results proposed can be exploited in human-robot teams. For instance, when the robot detects the position of a sensible target, it can guide the wrist of the operator in such position following an optimal path.

In the last years, wearable haptic technologies became very promising since they provide the users with tactile force feedback via small and wearable interfaces. However, they have no position sensing thus additional technologies like motion capture systems or expensive gloves are required. Recently, low cost hand tracking systems based on RGB-D cameras have been developed, however they suffer from lighting conditions and occlusions. In this paper we present a sensing glove based on inertial and magnetic sensors for hand tracking which can be combined with cutaneous devices for the rendering of the force feedback, thus producing a wearable sensing/actuation system. The sensing glove does not suffer from occlusion problems, it is wearable and cost effective however, since the employed sensors use the magnetometer to compensate the drift, they are sensitive to variations in the magnetic field. This property makes it challenging to interface the sensing glove with wearable devices since their motors generate variations in the magnetic field. Preliminary experiments showed the effectiveness of using inertial and magnetic sensors for hand tracking. A comparison between using the glove with and without the haptic devices was presented in order to compare the tracking performance when cutaneous devices are used.

Wearable robots have been mostly designed as exoskeletons, with segments and joints corresponding to those of the person they are coupled with. Exoskeletons are mainly employed to augment human body force and precision capabilities, or for rehabilitation purposes. More recently, new wearable robots resembling additional robotic limbs have been developed thanks to the progress in miniaturization and efficiency of mechanical and sensing components. However, wearable robotic extra limbs presented in the literature lack of effective haptic feedback systems. In this paper, we present a robotic extra finger coupled with a vibrotactile ring interface. The human user is able to control the motion of the robotic finger through a switch placed on the ring, while being provided with vibrotactile feedback about the forces exerted by the robotic finger on the environment. To understand how to control the vibrotactile interface to evoke the most effective cutaneous sensations, we executed perceptual experiments to evaluate its absolute and differential thresholds. We also carried out a pick-and-place experiment with ten subjects. Haptic feedback significantly improved the performance in task execution in terms of completion time, exerted force, and perceived effectiveness. All subjects preferred experimental conditions employing haptic feedback with respect to those not providing any force feedback.

This paper introduces a tactile rendering algorithm for wearable cutaneous devices that stimulate the skin through local contact surface modulation. The first step in the algorithm simulates contact between a skin model and virtual objects, and computes the contact surface to be rendered. The accuracy of this surface is maximized by simulating soft skin with its characteristic nonlinear behavior. The second step takes the desired contact surface as input, and computes the device configuration by solving an optimization problem, i.e., minimizing the deviation between the contact surface in the virtual environment and the contact surface rendered by the device. The method is implemented on a thimble-like wearable device.

In this paper a novel teleoperation framework for aerial robots that physically interact with the environment is presented. This framework allows to teleoperate the robot both in contact-free flight and in physical contact with the environment in order, e.g., to apply desired forces on objects of the environment. The framework is build upon an impedance-like indirect interaction force controller that allows to use standard underactuated aerial robots as force effectors. Haptic feedback from the master side enables the user to feel the contact forces exerted by the robot. An automatic potential field-based slowing-down policy is used by the robot to ensure a smooth transition between the contact-free motion phase and the force interaction phase. The effectiveness of the approach has been shown in extensive human-in-the-loop simulations including remote pressing of buttons on a surface and pushing a cart until it touches a wall.

In this paper we present a mathematical framework to describe the interaction between compliant hands and environmental constraints during grasping tasks. In the proposed model, we considered compliance at wrist, joint and contact level. We modeled the general case in which the hand is in contact with the object and the surrounding environment. All the other contact cases can be derived from the proposed system of equations. We performed several numerical simulation using the SynGrasp Matlab Toolbox to prove the consistency of the proposed model. We tested different combinations of compliance as well as different reference inputs for the hand/arm system considered. This work has to be intended as a tool for compliant hand designer since it allows to tune compliance at different levels before the real hand realization. Furthermore, the same framework can be used for compliant hand simulation in order to study the interaction with the environmental constrains and to plan complex manipulation tasks.

In this paper, we present a haptic guidance policy to steer the user along predefined paths, and we evaluate a predictive approach to compensate actuation delays that humans have when they are guided along a given trajectory via sensory stimuli. The proposed navigation policy exploits the nonholonomic nature of human locomotion in goal directed paths, which leads to a very simple guidance mechanism. The proposed method has been evaluated in a real scenario where seven human subjects were asked to walk along a set of predefined paths, and were guided via vibrotactile cues. Their poses as well as the related distances from the path have been recorded using an accurate optical tracking system. Results revealed that an average error of 0.24 m is achieved by using the proposed haptic policy, and that the predictive approach does not bring significant improvements to the path following problem for what concerns the distance error. On the contrary, the predictive approach achieved a definitely lower activation time of the haptic interfaces.

The flying hand is a robotic hand consisting of a swarm of UAVs able to grasp an object where each UAV contributes to the grasping task with a single contact point at the tooltip. The swarm of robots is teleoperated by a human hand whose fingertip motions are tracked, e.g., using an RGB-D camera. We solve the kinematic dissimilarity of this unique master-slave system using a multi-layered approach that includes: a hand interpreter that translates the fingertip motion in a desired motion for the object to be manipulated; a mapping algorithm that transforms the desired object motions into a suitable set of virtual points deviating from the planned contact points; a compliant force control for the case of quadrotor UAVs that allows to use them as indirect 3D force effectors. Visual feedback is also used as sensory substitution technique to provide a hint on the internal forces exerted on the object. We validate the approach with several human-in-the-loop simulations including the full physical model of the object, contact points and UAVs.

In this paper the problem of a quadrotor that physically interacts with the surrounding environment through a rigid tool is considered. We present a theoretical design that allows to exert an arbitrary 3D force by using a standard near-hovering controller that was originally developed for contact-free flight control. This is achieved by analytically solving the nonlinear system that relates the quadrotor state, the force exerted by the rigid tool on the environment, and the near-hovering controller action at the equilibrium points, during any generic contact. Stability of the equilibria for the most relevant actions (pushing, releasing, lifting, dropping, and left-right shifting) are proven by means of numerical analysis using the indirect Lyapunov method. An experimental platform, including a suitable tool design, has been developed and used to validate the theory with preliminary experiments.

Replicating the human hand capabilities is a great challenge in telemanipulation as well as in autonomous grasping and manipulation. One of the main issues is the difference between human and robotic hands in terms of kinematic structure, which does not allow a direct correlation of the joints. We recently proposed an object-based mapping algorithm able to replicate on several robotic hand models the human hand synergies. In such approach the virtual object shapes were a-priori defined (e.g. a sphere or an ellipsoid) and the transformation was represented as the composition of a rigid body motion and a scale variation. In this work, we introduce a generalization of the object-based mapping that overcomes the definition of a shape for the virtual object. We consider only a set of reference points on the hands. We estimate a homogeneous transformation matrix that represents how the human hand motion changes its reference point positions. The same transformation is then imposed to the reference points on the robotic hand and the joints values obtained through a kinematic inversion technique. The mapping approach is suitable also for telemanipulation scenarios where the hand joint motions are combined with a wrist displacement.

This paper proposes a novel use of haptic feedback for human navigation with a mobile robot. Assuming that a path-planner has provided a mobile robot with an obstacle-free trajectory, the vehicle must steer the human from an initial to a desired target position by only interacting with him/her via a custom-designed vibro-tactile bracelet. The subject is free to decide his/her own pace and a warning vibrational signal is generated by the bracelet only when a large deviation with respect to the planned trajectory is detected by the vision sensor on-board the robot. This leads to a cooperative navigation system that is less intrusive, more flexible and easy-to-use than the ones existing in literature. The effectiveness of the proposed system is demonstrated via extensive real-world experiments.

Needle insertion in soft-tissue is a minimally invasive surgical procedure which demands high accuracy. In this respect, robotic systems with autonomous control algorithms have been exploited as the main tool to achieve high accuracy and reliability. However, for reasons of safety and acceptance by the surgical community, autonomous robotic control is not desirable. Thus, it is necessary to focus more on techniques enabling clinicians to directly control the motion of surgical tools. In this work we address that challenge and present a novel teleoperated robotic system able to steer flexible needles. The proposed system tracks the position of the needle using an ultrasound imaging system, and, from that, it computes needle's ideal position and orientation to reach a given target. The master haptic interface then provides mixed kinesthetic-vibratory navigation cues about this ideal position and orientation to the clinician as she steers the needle. Six subjects carried out an experiment of teleoperated needle insertion into a soft-tissue phantom. They showed a mean targeting error of 1.36 mm. An additional experiment of remote teleoperation has been carried out to highlight the passivity-based stability of the proposed system.

Robotic prosthesis are usually intended as artificial device extensions replacing a missing part of a human body. A new approach regarding robotic limbs is presented here. A modular robot is used not only for replacing a missing part of the body but also as an extra-limb in order to enhance manipulation dexterity and enlarge the workspace of human beings. In this work, the model and control of an additional finger, the Sixth-Finger, is presented as a case study of this type of robotic limbs. The robotic finger has been placed on the wrist opposite to the hand palm. This solution allows to enlarge the hand workspace, increasing the grasp capability of the user. An object-based mapping algorithm is proposed to control the robotic extra-finger by interpreting the whole hand motion in grasping action. A four DoFs modular prototype is presented along with numerical simulations and real experiments. The proposed Sixth-Finger can lead to a wide range of applications in the direction of augmenting human capabilities through wearable robotics.

A study on the role of cutaneous and kinesthetic force feedback in teleoperation is presented. Cutaneous cues provide less transparency than kinesthetic force, but they do not affect the stability of the teleoperation system. On the other hand, kinesthesia provides a compelling illusion of telepresence but affects the stability of the haptic loop. However, when employing common grounded haptic interfaces, it is not possible to independently control the cutaneous and kinesthetic components of the interaction. For this reason, many control techniques ensure a stable interaction by scaling down both kinesthetic and cutaneous force feedback, even though acting on the cutaneous channel is not necessary. We discuss here the feasibility of a novel approach. It aims at improving the realism of the haptic rendering, while preserving its stability, by modulating cutaneous force to compensate for a lack of kinesthesia. We carried out two teleoperation experiments, evaluating (1) the role of cutaneous stimuli when reducing kinesthesia and (2) the extent to which an overactuation of the cutaneous channel can fully compensate for a lack of kinesthetic force feedback. Results showed that, to some extent, it is possible to compensate for a lack of kinesthesia with the aforementioned technique, without significant performance degradation. Moreover, users showed a high comfort level in using the proposed system.

This paper deals with haptic systems involving multiple human operators and devices with computational and communication delays. A method is proposed for the design of stabilizing controllers which also guarantee transparency, i.e., controllers are designed to mitigate the impact of delays and of the controllers themselves on the realism of the tactile interaction. The proposed approach exploits an extension of a previously developed passivity-based framework for stabilization combined with a special loop shaping-like technique. The design procedure involves the solution of a sequence of Linear Matrix Inequality (LMI) optimization problems.

In teleoperation and in particular in surgical robotics, it is important to avoid getting closer to certain forbidden areas typically limited by virtual constraints. In this paper we compare different sensory modalities, vibratory, auditory and visual, to convey information about constraint violation to the operator. We focus on which of these modalities can elicit the fastest reaction time on the user. An experiment was devised in which subjects were asked to slowly insert a virtual tool by means of a haptic interface, and retract it as soon as they hit an obstacle; such event triggered an alert signal. We evaluated different signals: auditory, vibrotactile, and visual, with two amplitude levels for audio and vibration. Lower reaction times were observed on the strong vibrotactile modality, followed by the weak vibrations and the loud auditory tone, although the latter was described as uncomfortable by the subjects. The vibrotactile feedback was described as pleasant by most subjects and appears promising for future developments.

This paper introduces a new approach to haptic feedback during teleoperated robot-assisted surgery. Haptic feedback allows to display to the surgeon the local mechanical properties of the tissue being manipulated, as well as additional information, such as navigation cues. However, when the same end-effector is used to present multiple types of information, there is the risk of confusing the sources of force feedback signals provided to the operator. The objective of this work is to study how to efficiently combine remote tissue sensing and haptic guidance, in order to make the surgeon aware of the source of the stimuli. We propose to use vibrotactile feedback to render navigation cues and kinesthetic feedback to reproduce the mechanical properties of the tissue. The viability of this approach is validated with two experiments where vibrotactile-guided navigation achieves promising performance and allows users to easily disambiguate forces due to the action of guiding constraints and forces due to the interaction with the remote tissue.

A study on the role of cutaneous and kinesthetic force feedback in teleoperation is presented. Cutaneous cues provide less transparency than kinesthetic force feedback but they do not affect the stability of the teleoperation system. On the other hand, kinesthesia provides a realistic illusion of telepresence but it affects the stability of the haptic loop. Several well-established control techniques ensure a stable interaction by scaling down force feedback as and when required, in order to satisfy the controller stability conditions (e.g., passivity). We here discuss the feasibility of a novel approach to improve the realism of the haptic rendering while preserving its stability: can cutaneous stimuli be employed to compensate for the lack of kinesthetic feedback required to guarantee the stability of the teleoperation loop? We carried out two experiments to evaluate the role of cutaneous cues in teleoperation and the performance improvement rate when compensating a lack of kinesthesia with cutaneous force. Results showed improved performance while employing the aforementioned compensation technique and a high comfort in using the proposed system.

SynGrasp is a MATLAB toolbox developed for the analysis of grasping, suitable both for robotic and human hands. It includes functions for the definition of hand kinematic structure and of the contact points with a grasped object. The coupling between joints induced by an underactuated control can be modeled. The hand modeling allows to define compliance at the contact, joint and actuator levels. The provided analysis functions can be used to investigate the main grasp properties: controllable forces and object displacement, manipulability analysis, grasp quality measures. Functions for the graphical representation of the hand, the object and the main analysis results are provided.

Underactuation represents a solution to reduce the number of Degrees of Freddom (DoF) of robotic hands. Altough reducing the number of DoFs in general limits the ability to perform many and different types of grasp, the use of springs in the structure improves the compliance of the grasp and mitigates the loss of generality due to the reduction of DoFs in the mechanical structure. The use of active and passive elastic elements improves robustness of the whole grasp. In this paper we evaluate the grasp stiffness which depends on the structural compliance of hand links and joints and of the contacts, and on the gains of impedance controllers. A quasi-static model of the grasp for underactuated hands is presented and used to explicitly compute the grasp compliance.

A novel idea for improving transparency of teleoperation systems with force feedback is presented. This approach is based on the idea of sensory subtraction presented in [12], and consists of providing the operator with independently controlled kinesthetic and cutaneous feedback to improve the realism of haptic rendering of the remote environment (i.e., transparency), while preserving stability. More specifically, cutaneous force feedback is employed to recover transparency when a lack of kinesthetic feedback has to be enforced to keep the teleoperation loop stable. The viability of this approach is demonstrated with two experiments of teleoperated needle insertion. Results showed improved performance with respect to common control techniques not employing the proposed cutaneous compensation.

This paper presents a bilateral telemanipulation framework where the master and slave sub-systems have different kinematic structures. A virtual object is defined on the master and slave sides and used to capture the human hand motion and to compute the related force feedback. The force feedback is determined imposing that the same wrench acts on the master and slave virtual objects. An abstraction from the sub-system structures is obtained focusing on the effects produced on the manipulated object. The proposed approach has been tested with an experimental setup consisting of two haptic interfaces able to capture index and thumb motions on the master side and a DLR-HIT Hand II as slave sub-system.

Replicating human hand capabilities on robotic hands is a great challenge in robotics. The high complexity of mechanical and actuation systems of available robotic device can be, however, considerably mitigated if a human inspired control is considered. In this paper the application of an object-based mapping to the control of robot hands is presented. The basic idea is to use a virtual object, e.g. a virtual sphere, to capture human hand motion generating suitable reference signals for a low level controller of the robotic hand. The low level controller considered, which shares the idea of virtual object to reduce the complexity of the control, is the static Intrinsically Passive Controller (s-IPC). This controller is inspired by the dynamic IPC, but provides a simpler and more efficient implementation. The proposed approach allows to map motion of a human hand model, controlled on the reduced subspace of postural synergies, onto robotic hands guaranteeing the stability of the robotic grasp. This concept, which has been experimentally validated in the paper, can be exploit for complex planning methods or used in telemanipulation application.

This paper presents a new algorithm based on previous results of the authors, for the estimation of the yaw angle of an omnidirectional camera/robot undergoing a 6-DoF rigid motion. Our real-time algorithm is uncalibrated, robust to noisy data, and it only relies on the projection of 3-D parallel lines as image features. Numerical and real-world experiments conducted with an eye-in-hand robot manipulator, which we used to simulate the 3-D motion of a Micro unmanned Aerial Vehicle (MAV), show the accuracy and reliability of our estimation algorithm.

One of the major limitations to the use of advanced robotic hands in industries is the complexity of the control system design due to the large number of motors needed to actuate their degrees of freedom. It is our belief that the development of a unified control framework for robotic hands will allow us to extend the use of these devices in many areas. Borrowing the terminology from software engineering, there is a need for middleware solutions to control the robotic hands independently from their specific kinematics and focus only on the manipulation tasks. To simplify and generalize the control of robotic hands, we take inspiration from studies in neuroscience concerning the sensorimotor organization of the human hand. These studies demonstrated that, notwithstanding the complexity of the hand, a few variables are able to account for most of the variance in the patterns of configurations and movements. The reduced set of parameters that humans effectively use to control their hands, which are known in the literature as synergies, can represent the set of words for the unified control language of robotic hands, provided that we solve the problem of mapping human hand synergies to actions of the robotic hands. In this study, we propose a mapping designed in the manipulated object domain in order to ensure a high level of generality with respect to the many dissimilar kinematics of robotic hands. The role of the object is played by a virtual sphere, whose radius and center position change dynamically, and the role of the human hand is played by a hand model referred to as “paradigmatic hand,” which is able to capture the idea of synergies in human hands.

To adapt to many different objects and tasks, hands are very complex systems with many degrees of freedom (DoFs), sensors, and actuators. In robotics, such complexity comes at the cost of size and weight of the hardware of devices, but it strongly affects also the ease of their programming. A possible approach to simplification consists in coupling some of the DOFs, thus affording a reduction of the number of effective inputs, and eventually leading to more efficient, simpler, and reliable designs. Such coupling can be at the software level, to achieve faster, more intuitive programmability or at the hardware level, through either rigid or compliant physical couplings between joints. Physical coupling between actuators and simplification of control through the reduction of independent inputs is also an often-reported interpretation of human hand movement data, where studies have demonstrated that few “postural synergies” explain most of the variance in hand configurations used to grasp different objects. Together with beneficial simplifications, the reduction of the number of independent inputs to a few coupled motions or “synergies” has also an impact on the ability of the hand to dexterously control grasp forces and in-hand manipulation. This paper aims to develop tools that establish how many synergies should be involved in a grasp to guarantee stability and efficiency, depending on the task and on the hand embodiment. Through the analysis of a quasi-static model, grasp structural properties related to contact force and object motion controllability are defined. Different compliant sources are considered, for a generalization of the discussion. In particular, a compliant model for synergies assumed, referred to as “soft synergies,” is discussed. The controllable internal forces and motions of the grasped object are related to the actuated inputs. This paper investigates to what extent a hand with many joints can exploit postural synergies to control force and motion of the grasped object.

Compliance in multifingered hand improves grasp stability and effectiveness of the manipulation tasks. Compliance of robotic hands depends mainly on the joint control parameters, on the mechanical design of the hand, as joint passive springs, and on the contact properties. In object grasping the primary task of the robotic hand is the control of internal forces which allows to satisfy the contact constraints and consequently to guarantee a stable grasp of the object. When compliance is an essential element of the multifingered hand, and the control of the internal forces is not designed to be decoupled from the object motion, it happens that a change in the internal forces causes the object trajectory to deviate from the planned path with consequent performance degradation. This paper studies the structural conditions to design an internal force controller decoupled from object motions. The analysis is constructive and a controller of internal forces is proposed. We will refer to this controller as object motion-decoupled control of internal forces. The force controller has been successfully tested on a realistic model of the DLR Hand II. This controller provides a trajectory interface allowing to vary the internal forces (and to specify object motions) of an underactuated hand, which can be used by higher-level modules, e.g. planning tools.

Wearable haptic devices with poor position sensing are combined with the Kinect depth sensor by Microsoft. A heuristic hand tracker has been developed. It allows for the animation of the hand avatar in the virtual reality and the implementation of the force rendering algorithm: the position of the fingertips is measured by the hand tracker designed and optimized for Kinect, and the rendering algorithm computes the contact forces for wearable haptic display. Preliminary experiments with qualitative results show the effectiveness of the idea of combining Kinect and wearable haptics.

The control of internal forces is one of the key issues in grasping. When the robotic hand is compliant, for instance with passive springs at the joints, and the number of controlled variables is low, as shown in recent works for underactuated hands, it is possible that the control of internal forces implies the motion of the manipulated object. This paper deals with this issue and studies the structural conditions for the control of internal forces which do not involve any motion of the grasped object. The analysis is constructive and a controller of internal forces is proposed. Note that guaranteeing zero motion of the object while controlling internal forces is paramount in robotic manipulation when the task requires large accuracy.

The Kuka Control Toolbox (KCT) is a collection of MATLAB functions for motion control of KUKA robot manipulators, developed to offer an intuitive and high-level programming interface to the user. The toolbox, which is compatible with all 6 DOF small and low payload KUKA robots that use the Eth.RSIXML, runs on a remote computer connected with the KUKA controller via TCP/IP. KCT includes more than 30 functions, spanning operations such as forward and inverse kinematics computation, point-to-point joint and Cartesian control, trajectory generation, graphical display and diagnostics. The flexibility, ease of use and reliability of the toolbox is demonstrated through two applicative examples.

The paper deals with a general class of leader-follower formations of unicycle robots induced by a constraint function that depends on the position and the orientation of the vehicles. We study the flexibility of such formations by introducing the notion of formation internal dynamics, characterize its equilibria and give sufficient geometric conditions for their existence. In particular, we show that the displacement and the relative orientation of each follower with respect to the leader's reference frame are fixed if and only if the robots either move along circular paths or parallel straight lines. These equilibrium configurations always exist if the trajectory of the leader is a circle of sufficiently small curvature or a straight line.

This paper presents some preliminary results on RemoTouch, a system allowing to perform experiences of remote touch. The system consists of an avatar equipped with an instrumented glove and a user wearing tactile displays allowing to feel the remote tactile interaction. The main features of RemoTouch are that it is a wearable system and that a human avatar is used to collect remote tactile interaction data. New paradigms of tactile communication can be designed around the RemoTouch system. Two simple experiences are reported to show the potential of the proposed remote touch architecture.

Haptic interfaces in Augmented Reality scenarios are an efficient way to enhance the interaction with a virtual world. We introduce a new system that involves both hands in virtual object experience. We render contemporary shape and weight of a virtual object, merged in a real world environment, using a commercial haptic interface and a new kind of finger-worn device. We test the system with an experimental setup where a virtual cube is placed over a real marker. The system developed can be used in several applications of augmented reality where rendering only the object shape is not enough to perceive the virtual world. It can also lead towards the introduction of more wearable devices in the haptics augmented reality context.

Planar catadioptric stereo vision sensors (PCS) combine a pinhole camera with two or more planar mirrors. PCS have recently received an increasing attention since a stereo view can be easily obtained without the need of exact multi-camera synchronization and calibration. In this paper we present a rigorous analytical treatment of the imaging geometry of PCS, propose new mirror calibration algorithms and introduce new multi-view properties that can be used for eye-in-hand camera localization. The effectiveness of the algorithms is shown via extensive simulation and real-data experiments on a robotic manipulator.

The paper proposes an original solution to the range identification problem for perspective dynamical systems. The depth of a static point observed by a pinhole camera undergoing a predefined 3-D motion, is estimated from its 2-D projection on the image plane. The proposed nonlinear observer relies on the immersion and invariance (I&I) methodology and offers several advantages over the existing range estimators. The paper also provides an analytical study of nonlinear observability performed with the extended output Jacobian. Extensive simulation experiments illustrate the theory and show the effectiveness of the proposed design.

The paper studies the cyclic pursuit problem in presence of connectivity constraints among single-integrator agents. The robots, each one pursuing its leading neighbor along the line of sight rotated by a common offset angle, are supposed to have a communication set described by a disk of constant radius. Given the initial position of the agents, we determine the communication radii that preserve the connectivity of the robots while they rendezvous at a point or converge to an evenly spaced circle formation. The special case that the initial condition is a linear combination of the eigenvectors of the dynamic matrix of the system, is studied in detail. On the other hand, given the communication radii, we find the set of initial conditions that guarantee the robots remain always connected. As a final contribution, once assigned a ldquonon-optimalrdquo radius, we study the stability of the hybrid system describing the dynamics of the robotic network under variable connectivity levels.

The paper proposes a new geometric approach to the stabilization of a hierarchical formation of unicycle robots. Hierarchical formations consist of elementary leader-follower units disposed on a rooted tree: each follower sees its relative leader as a fixed point in its own reference frame. Robots' linear velocity and trajectory curvature are forced to satisfy some given bounds. The major contribution of the paper is to study the effect of these bounds on the admissible trajectories of the main leader. In particular, we provide recursive formulas for the maximum velocity and curvature allowed for the main leader, so that the robots can achieve the desired formation while respecting their input constraints. An original formation control law is proposed and the asymptotic stabilization is proved. Simulation experiments illustrate the theory and show the effectiveness of the proposed designs.

This paper deals with vision-based localization for leader–follower formation control. Each unicycle robot is equipped with a panoramic camera that only provides the view angle to the other robots. The localization problem is studied using a new observability condition valid for general nonlinear systems and based on the extended output Jacobian. This allows us to identify those robot motions that preserve the system observability and those that render it nonobservable. The state of the leader–follower system is estimated via the extended Kalman filter, and an input-state feedback control law is designed to stabilize the formation. Simulations and real-data experiments confirm the theoretical results and show the effectiveness of the proposed formation control.

The paper introduces a new vision-based range estimator based upon the Immersion and Invariance (I&I) methodology, for leader-follower formation control. The proposed reduced-order nonlinear observer achieves global exponential convergence of the observation error to zero and it is extremely simple to implement and to tune. A Lyapunov analysis is provided to show the stability of the closed-loop system arising from the combination of the range estimator and an input-state feedback controller. Simulation experiments illustrate the theory and show the effectiveness of the proposed design.

The increasing demand for virtual reality applications in several scientific disciplines feeds new research perspectives dealing with robotics, automation, and computer science. In this context, one of the topics is the design of advanced force-feedback devices allowing not only kinesthetic interaction with virtual objects but also locomotion and navigation inside virtual worlds. This has the main advantage to stimulate human vestibular apparatus, thus increasing the overall realism of simulation. Particularly, this paper deals with mobile haptic interfaces (MHIs), built by combining standard force-feedback devices with mobile platforms. We investigated which factors may affect the transparency of this kind of devices, identifying in mobile robot dynamics a possible cause of loss of transparency. Hence, in this paper, we present a method to analyze dynamic performance of an MHI and some basic guidelines to design controller in order to meet desired specifications. Experimental validation of the theoretical results is reported.

The paper focuses on leader-follower formations of nonholonomic mobile robots. A formation control alternative to those existing in the literature is introduced. We show that the geometry of the formation imposes a bound on the maximum admissible curvature of leader trajectory. A peculiar feature of the proposed strategy is that the followers position is not rigidly fixed with respect to the leader reference frame but varies in suitable cones centered in the leader reference frame. Our approach also applies to hierarchical multirobot formations described by rooted tree graphs. Simulation experiments confirm the effectiveness of the proposed control schemes.

In real object manipulation, the deformation of the fingerpads along the contact surfaces provides local information about the geometry of the object the subject is manipulating, even in absence of vision and any exploratory movement. In virtual reality with haptic feedback this kind of stimulation is not available because the haptic devices currently available allow to simulate a contact point force interaction thus preventing the deformation of the fingerpads. The aim of this work is that of proposing a novel contact model to augment the information conveyed during kinesthetic interaction with single-point haptic devices. We extended the classic god-point algorithm by using a pseudo-ellipsoidal force field that creates anisotropic compliance in the neighborhood of the contact point. We performed several experiments in order to verify that such contact model can provide information about contact surface orientation even in absence of vision and of free voluntary exploration. The main finding was that participants could identify the orientation of the contact surface when the compliance was maximum in the tangential plane by using small exploratory movements allowed by the penalty-based contact model.

This paper focuses on leader-follower formations of mobile robots equipped with panoramic cameras and extend earlier works in the literature addressing both the vision-based localization and control problems. First, a new sufficient analytical condition for localizability is proved and used to shed light on the geometrical meaning of formation localization using uncalibrated vision sensors, here performed with the unscented Kalman filter. Second, we design a feedback control law based on dynamic extension in order to extend the applicability of our control scheme also to the case of distant robots.

Due to their panoramic field of view, catadioptric cameras are becoming ubiquitous in many robotics and computer vision applications. Catadioptric cameras with a unique viewpoint are of primary interest, among these is the case where the reflective surface is a parabolic mirror and the camera satisfies the orthographic projection model and which we call paracatadioptric. We here present a new geometrical property (called disparity-circles property) for paracatadioptric cameras and use it to design a video compass algorithm that can compute the 1-axis rotation angle between two views of at least two parallel lines, without any need of internal camera calibration parameters. We present a linear closed form solution suitable for real-time implementation. We then study the performances of our algorithm, its sensitivity to image noise and propose also experimental results with a paracatadioptric camera mounted on a mobile robotic platform.

For a human-robot interface it is important to have a good model of how the human subject operates. However, since such a model is difficult to obtain, then the robotics interface must observe accurately the subject's behaviour when interacting with him. We present here a new human-robot interface for active interaction with the cognitive and emotional human domains. Since eye movements convey a lot of information about one subject's cognitive and emotive status, we have designed a new human-robot interface which uses a video-based Eye-Tracker (ET) to observe the subject's line of gaze. Since we are also interested in using our interface for studying and treating depression, our interface can send stimulating inputs to the subject using both a Transcranial Magnetic Stimulator (TMS) and a visual stimulus. The latter elicits the subject's emotions and consists of a set of pictures of facial expressions, which have been shown according to a novel visualization protocol, called Memory-Guided Filtering (MGF). Its effectiveness has been verified by means of many experimental results. We also present the application of our human-robot interface for preliminary studies concerning new cognitive rehabilitation strategies in depression.

We present an image-based visual servoing strategy for driving a nonholonomic mobile robot equipped with a pinhole camera toward a desired configuration. The proposed approach, which exploits the epipolar geometry defined by the current and desired camera views, does not need any knowledge of the 3-D scene geometry. The control scheme is divided into two steps. In the first, using an approximate input-output linearizing feedback, the epipoles are zeroed so as to align the robot with the goal. Feature points are then used in the second translational step to reach the desired configuration. Asymptotic convergence to the desired configuration is proven, both in the calibrated and partially calibrated case. Simulation and experimental results show the effectiveness of the proposed control scheme

We present an image-based visual servoing strategy for nonholonomic mobile robot equipped with a central catadioptric camera. This kind of vision sensor combines lens and mirrors to enlarge the field of view. The proposed approach, which exploits the epipolar geometry defined by the current and the desired camera views, does not need any knowledge of the 3-D scene geometry. The control scheme is divided in two steps. In the first one, the epipoles are used together with an approximate input-output linearizing feedback to align the robot with the goal. Feature points are then used in the second translation step to reach the desired configuration. Global asymptotic convergence is proven. Simulation and experimental results show the effectiveness of the proposed control scheme

This paper presents how to detect planes from a set of corresponding points with a stereo camera system. We show that, in the presence of two cameras aligned to the same orientation, it is possible to compute the normal vector to a plane by using only three corresponding points whereas with traditional methods this computation requires at least four points and the decomposition of the homography matrix. We obtain the triangulation of the set of features and we compute for every triangle its normal vector. By grouping adjacent triangles with equal normal we are able to select all the points belonging to the same plane. The method does not require any information about the camera calibration or the camera relative translation. Simulation and experiments on real images validate the proposed algorithm

In this paper we present the V-GRAPH, a framework for bounded-time collision detection for point-like haptic interactions. This frame-work employs strategies similar to those used by the Lin-Canny and Dobkin-Kirkpatrick algorithms but, differently from these ones, it uses a partition of the space focused on vertices only, which al-lows both for an easier implementation and for usage with non-convex objects without the need for splitting the original mesh. In a preprocessing phase the mesh is analyzed to extract neighboring information based on Voronoi theory, then this data is used at run-time in a greedy visit exploiting motion coherence to achieve fast proximity queries. Finally standard segment-triangle intersection tests are eventually carried out to identify the exact point of collision. Moreover the framework can be easily extended to multiple levels of detail. Computational analysis and experimental results show that execution times are independent from mesh complexity, achieving same running times even on models composed by mil-lions of polygons. These features make it particularly suited for virtual museum and digital sculpting applications. Implementation is straightforward and freely available tools can be used for pre-processing.

The problem of establishing if it is possible to reach the desired location keeping all features in the field of view and following a straight line is considered. The proposed approach is based on the polynomial parameterization of the camera path and allows one to find the path that follows a straight line and maximizes the distance of the image trajectories from the screen boundary.

This paper presents an epipolar based visual servoing for mobile robots equipped with a panoramic camera. The proposed visual servoing is based on the epipolar geometry and exploits the auto-epipolar property, a special configuration for the epipoles which occurs when the desired and the current views undergo a pure translation. This occurrence is detectable observing when the bi-osculating mirror conics co-intersect at the two epipoles. The auto epipolar condition enables our controller to retrieve the equal orientation between target and current camera. Translation is performed by exploiting the epipoles. Simulated experiments and Lyapunov-based stability analysis demonstrate the parametric robustness of the proposed method.

This paper presents the Automatic Control Telelab (ACT), a remote laboratory for education in robotics and automation developed in Siena. A special attention is devoted to the new ACT process, a Lego mobile robot, which has been recently added to the telelab. Remote users can control the Lego mobile robot, and all the other processes, using an Internet browser. Moreover users can design new controllers by means of the Matlab/Simulink environment. The ACT home page is http://www.dii.unisi.it//spl sim/control/act.

A new image-based visual servoing algorithm is presented for nonholonomic mobile robots. The algorithm, based on epipolar geometry, consists of three independent and sequential steps making use of both the estimated epipoles and the image features. In particular, due to the nonlinear dynamics of the camera-robot system, an input-output feedback linearizing control law is used during the second step. Simulations results are presented to validate the proposed visual servoing technique.

We present a purely rotational visual servoing algorithm, which aligns the orientation between two cameras at different locations in space. Specifically, our kinematic controller steers a set of so-called bi-tangent lines to intersect at the epipole using a purely image-based bi-tangent line Jacobian. Bi-tangent lines, i.e. lines joining corresponding features on the superposition of two views of a scene, can be defined for both points and contours, so we apply our controller to both feature types. Simulated experiments demonstrate the parametric robustness of the proposed method.

In this paper we present a new method for real-time interactive haptic and graphic rendering of complex objects locally deformed by multiple contacts. Core algorithms have been designed to be executable also on videoboard's GPU, thus taking advantage of parallel matrix and vector computational power. Although complex physical simulation has been simplified to run on GPUs, results are characterized by high visio-tactile realism perceived by users. Graphical rendering algorithms can be easily added to pre-existing vertex shaders/programs. The proposed method makes use of common triangular meshes, thus making the method a good choice when adding haptic feedback to existing graphical applications.

A visual servoing strategy for keeping features in the field of view is proposed which consists of a switching among position-based control strategies and backward motion. In the absence of uncertainty on the extrinsic parameters, all features are kept in the field of view. Moreover, if the intrinsic parameters are also known, the trajectory length is minimized in the rotational space and, for some cases, also minimized in the translational space. Simulation results also show a certain degree of robustness against uncertainty on the intrinsic parameters.

In this paper, a visual servoing strategy for dealing with the problem of keeping the observed points in the camera field of view is proposed. The approach consists of a switching control law based on camera displacement estimation and regulated from the position of the points in the image. In absence of uncertainties on the intrinsic parameters and optical axis direction, global stability is achieved and all points are kept in the field of view. Moreover, the trajectory length is minimized in the rotational space and, for some cases, also minimized in the translational one. Robustness against uncertainties is also guaranteed.

Ultrasound technologies have been widely used in gynecology and obstetrics. Modern ultrasound systems allow the reconstruction of a 3D model of the subject being scanned. Even though visual interfaces have reached very high standards, the problem of representing a 3D image on a 2D computer screen still exists. Moreover, no physical interaction is possible with such model. The FeTouch system, developed at Siena University in the last two years, partially solves such issues by using stereo visual feedback and haptic devices. While the system can be used with any 3D model obtained from ultrasound scans, its current prime use is to allow mothers to interact with a model of the fetus they are carrying. The system, which is freely available on the project web page, has been tested on twelve cases which have been monitored by doctors at Siena Hospital.

A novel visual servoing method is presented. The algorithm works for both apparent contours and point features and does not require any information about the internal camera parameters. The proposed visual servoing is based on the epipolar geometry and exploits the autoepipolar property, a special configuration for the epipoles which occurs when the desired and current views undergo a pure translation. This occurrence is simply detectable from special line conditions on the overlapped current and desired images. Experiments are presented to validate the proposed visual servoing.

This paper proposes a visual servoing algorithm for hand-eye robotic system based on epipolar geometry. The control law is based on the estimation of the epipoles position obtained by points correspondences extracted from the current and target images. The camera-robot motion is computed from the observation of the epipoles coordinates. Only the principal camera point is assumed to be known but not the other intrinsic parameters. Experimental results are reported to validate the visual servoing algorithm proposed.

A visual servoing algorithm for mobile robots is proposed. The main feature of the algorithm is that it exploits object profiles rather than solving correspondence problems using object features or texture. This property is crucial for mobile robot navigation in unstructured environments where the 3D scene exhibits only surfaces whose main features are their apparent contours. The framework is based on the epipolar geometry, which is recovered from object profiles and epipolar tangencies. Special symmetry conditions of epipoles are used to generate the mobile robot control law. For the sake of simplicity, mobile robot kinematics is assumed to be holonomic and the camera intrinsic parameters are assumed partially known. Such assumption can be relaxed to extend the application field of the approach.

A nonhonolomic vehicle is stabilized to a desired pose through a visual servoing technique. The vision-based regulation of the nonholonomic vehicle proposed is built through a discontinuous change of coordinates and Lyapunov-based design, which ensure asymptotic stability of the closed-loop visual system. A dynamic estimation procedure, based on the optical flow equations, is also presented to deal with uncertainties in the obsereved environment. Simulations results on an autonomous mobile robot are reported, that show the practicality of the proposed approach.

Robotic grasps exhibiting visco-elastic contact interactions with the manipulated object are considered. Control of internal forces is investigated. The presence of nonnegligible compliance at contacts, implies that the object dynamics cannot be neglected when attempting to control internal forces without affecting the object position. A dynamic internal force control is proposed. It is decoupled with respect to the rigid-body object motions.

We study the differential kinematics and the kineto-static manipulability indices of multiple cooperating robot arms, including active and passive joints. The kinematic manipulability indices are derived extending previous results on cooperating robots without passive joints. The force manipulability analysis for cooperative robot systems cannot be straightforwardly derived by "duality" arguments as it can with conventional arms, rather a distinction between active and passive force manipulability must be introduced. Results in the paper apply directly to the analysis of cooperating robots, parallel robots, dextrous robotic hands and legged vehicles, and, in general, to closed kinematic chains.

The nonholonomy exhibited by kinematic systems consisting of bodies rolling on top of each other can be used for the purpose of building dexterous mechanisms with a minimum hardware complication. Such a desirable engineering feature can be fully exploited, however, only if the capability of planning and controlling the rolling motions of arbitrary objects is achieved. In this paper we present recent advances of both theoretical and experimental natures towards realizing a robot gripper for manipulation of objects whose shape is not known a priori, but is reconstructed as manipulation proceeds.

We study the differential kinematics and the kineto-static manipulability indices of multiple cooperating robot arms, including active and passive joints. The kinetic manipulability indices are derived as a simple extension of previous results on cooperating robots without passive joints. The force manipulability analysis for cooperative robot systems can not be derived by "duality" arguments as it can with conventional arms, rather a distinction between active and passive force manipulability is necessary. Results in the paper apply directly to the analysis of simply closed kinematic chains, and can be extended to multiply closed kinematic chains.

We present a geometric approach to the dynamic analysis of manipulation systems of a rather general class, including some important types of manipulators as, e.g., cooperating, super-articulated, and whole-arm manipulators. The focus is in particular on simple industry-oriented devices, for which a minimalistic design approach requires a clear understanding of mobility and graspability properties in the presence of kinematic defectivity. The paper discusses the dynamics of these systems, and considers how their structural properties (in the classical system-theoretic sense, i.e., stability, controllability, observability, etc.) are related to frequently used concepts in robotics such as "redundancy", "graspability", "mobility", and "indeterminacy". Less common or novel concepts, such as those of "defectivity," "hyperstaticity," and "dynamic graspability", are elicited and/or enlightened by this study. Some important practical consequences of the limited control possibilities of defective systems are thus put into evidence. Finally, a standard form of the dynamics of general manipulation systems is provided as a compact and readable synopsis of the dynamic structure. The form is a valuable tool for synthesizing dynamic controllers for such systems, especially suited to geometric control design methods.

In this paper we describe an experimental apparatus developed in our laboratory for research and advanced teaching purposes. The device consists of an untethered spherical vehicle that autonomously rolls on the laboratory floor, and can reach arbitrary positions and orientations in the environment. The kinematics of the vehicle are nonholonomic and result from the combination of the kinematics of two classical nonholonomic systems, namely, a unicycle and a plate-ball system. The "SPHERICLE" introduces features that are new with respect to the two systems.

The theory of force and dynamic manipulability for general systems of multiple co-operating robot manipulators is developed. Manipulability analysis refers to the study of the performance of the system regarding to the mechanical transformation of inputs (forces and torques at actuated joints) into outputs (forces and torques exchanged with the environment or accelerations of a reference member), in relation to different configurations of the system and different directions in the input and output spaces. For this purpose, the concept of manipulability ellipsoids for single robot arms is generalized so as to encompass multi-limb co-operating systems with general kinematic structure.

We focus on the problem of controlling a manipulator so as to trade a desired object trajectory, while guaranteeing that contact forces comply with contact constraints (friction bounds, etc.). When dealing with kinematically defective systems, it is not possible in general to assign arbitrary trajectories of object motions and contact forces. To understand what restrictions position and force reference trajectories should exhibit in order to be feasible by a given system, is the central issue of this work.

Considers the structural properties of the dynamics of robotic manipulation systems of a rather general class, including multiple cooperating, possibly whole-arm limbs, interacting with a manipulated object by means of contacts. A geometric approach to the analysis of the linearized dynamics of such systems is presented, which provides much insight in some of their intrinsic characteristics in the light of classical system-theoretic concepts such as controllability, observability, and canonical forms.

We present a general framework for the modelling of a class of mechanical systems for robotic manipulation, consisting of articulated limbs with redundant tendinous actuation and unilateral constraints. Such systems, that include biomorphically designed devices, are regarded as a collection of rigid bodies, interacting through connections that model both joints and contacts with virtual springs. Methods previously developed for the analysis of force distribution in multiple whole-limb manipulation are generalised to this broader class of mechanisms, and are shown to provide a basis for the control of co-contraction and internal forces that guarantee proper operation of the system.>