Robots are no longer just tools—they are becoming social agents that can shape how we engage with culture. This study examines what influences visitors’ perceptions of an autonomous museum guide robot, focusing not only on technical capabilities but also on human-centered factors. In a maritime exhibition, 34 participants interacted with a fully autonomous, LLM-powered robot acting as a museum guide. Using self-report questionnaires, we explored how individual differences - age and prior experience with robots — interacted with experimental conditions to shape participants’ impressions of the robot. Our findings suggest that these personal factors significantly affect how visitors evaluate the robot, suggesting that effective design must reflect the diversity of users’ experiences and expectations. By acknowledging the complexity of human-robot interaction, we move closer to creating robotic guides that are not only functional but also socially attuned.

The development of prosthetic feet that closely replicate the natural biomechanics of the human foot remains a significant challenge in prosthetics engineering. This paper presents the design and testing of a novel agonist-antagonist architecture for the ankle joint of a passive prosthetic foot featuring an adaptive sole. The ankle mechanism, inspired by the dynamics of the human leg-ankle-foot complex, utilizes compliant elements in an agonist-antagonist configuration to passively achieve an ankle torque close to that of a sound ankle without the need for external actuation. Concurrently, the adaptive sole adjusts its shape in response to different terrains, potentially improving stability and comfort for the user. The theoretical model underlying the proposed design is presented, followed by a preliminary validation through simulations. Finally, a prototype based on the new architecture is tested by a healthy subject using customized walking boots, demonstrating its potential to improve the functional performance of prosthetic feet in diverse environments.

This paper presents a shear-based control scheme for grasping and manipulating delicate objects with a Pisa/IIT anthropomorphic SoftHand equipped with soft biomimetic tactile sensors on all five fingertips. These ‘microTac’ tactile sensors are miniature versions of the TacTip vision-based tactile sensor, and can extract precise contact geometry and force information at each fingertip for use as feedback into a controller to modulate the grasp while a held object is manipulated. Using a parallel processing pipeline, we asynchronously capture tactile images and predict contact pose and force from multiple tactile sensors. Consistent pose and force models across all sensors are developed using supervised deep learning with transfer learning techniques. We then develop a grasp control framework that uses contact force feedback from all fingertip sensors simultaneously, allowing the hand to safely handle delicate objects even under external disturbances. This control framework is applied to several grasp-manipulation experiments: first, retaining a flexible cup in a grasp without crushing it under changes in object weight; second, a pouring task where the center of mass of the cup changes dynamically; and third, a tactile-driven leader-follower task where a human guides a held object. These manipulation tasks demonstrate more human- like dexterity with underactuated robotic hands by using fast reflexive control from tactile sensing.

Intuitively, prostheses with user-controllable stiffness could mimic the intrinsic behavior of the human musculoskeletal system, promoting safe and natural interactions and task adaptability in real-world scenarios. However, prosthetic design often disregards compliance because of the additional complexity, weight, and needed control channels. This article focuses on designing a variable stiffness actuator (VSA) with weight, size, and performance compatible with prosthetic applications, addressing its implementation for the elbow joint. While a direct biomimetic approach suggests adopting an agonist-antagonist (AA) layout to replicate the biceps and triceps brachii with elastic actuation, this solution is not optimal to accommodate the varied morphologies of residual limbs. Instead, we employed the AA layout to craft an elbow prosthesis fully contained in the user's forearm, catering to individuals with distal transhumeral amputations. In addition, we introduce a variant of this design where the two motors are split in the upper arm and forearm to distribute mass and volume more evenly along the bionic limb, enhancing comfort for patients with more proximal amputation levels. We characterize and validate our approach, demonstrating that both architectures meet the target requirements for an elbow prosthesis. The system attains the desired 120$^{\circ }$range of motion, achieves the target stiffness range of [2, 60] N$\cdot$m/rad, and can actively lift up to 3 kg. Our novel design reduces weight by up to 50% compared to existing VSAs for elbow prostheses while achieving performance comparable to the state of the art. Case studies suggest that passive and variable compliance could enable robust and safe interactions and task adaptability in the real world.

Endowing robots with advanced tactile abilities based on biomimicry involves designing human-like tactile sensors, computational models, and motor control policies to enhance contact information retrieval. Here, we consider compliance discrimination with a soft biomimetic tactile optical sensor (TacTip). In previous work, we proposed a vision-based approach derived from a computational model of human tactile perception to discriminate object compliance with the TacTip, based on contact area spread computation over the indenting force. In this work, we first increased the robustness of our vision-based method with a more precise estimation of the initial contact area condition, which enables correct compliance estimation also when the probing direction is other than normal to the specimen surface. Then, we integrated within our validated framework the mechanisms of internal muscular regulation (co-contraction) that humans adopt during object compliance probing, to maximize the information uptake. To this aim, we used human co-contraction patterns extracted during object softness probing to control a Variable Stiffness Actuator (that emulates the agonistic-antagonistic behavior of human muscles), which is used to actuate the indenter system endowed with the TacTip for object compliance exploration. We found that our model-based approach for compliance discrimination, fed with more precisely estimated initial conditions, significantly improves with the human-inspired impedance regulation, with respect to the usage of a rigid actuator.

This study presents the Prosthetic Upper-Limb Sensory Enhancement (PULSE), a novel dual feedback device completely integrated into a prosthetic socket. The core of the system includes two compact vibrotactile actuators and two silicone chambers in contact with the user’s skin. These components provide high-frequency tactile cues for initial contact and surface information (e.g. texture) as well as pressure stimuli related to grasping force. Ten able-bodied participants and one subject with limb loss validated the system, accomplishing an object discrimination task in two different modalities (with and without the feedback). Standardized questionnaires evaluate users’ satisfaction and workload, enabling a systematic and robust device assessment. The results show that the PULSE device enhanced performance compared to its absence without causing discomfort for a prosthetic user and able-bodied participants. The findings highlight the potential of dual haptic feedback to enhance sensory perception in prosthetic applications and offer valuable insights for future prosthetic design.

Robot feet are crucial for maintaining dynamic stability and propelling the body during walking, especially on uneven terrains. Traditionally, robot feet were mostly designed as flat and stiff pieces of metal, which meets its limitations when the robot is required to step on irregular grounds, e.g., stones. While one could think that adding compliance under such feet would solve the problem, this is not the case. To address this problem, we introduced the SoftFoot, an adaptive foot design that can enhance walking performance over irregular grounds. The proposed design is completely passive and varies its shape and stiffness based on the exerted forces, through a system of pulley, tendons, and springs opportunely placed in the structure. This article outlines the motivation behind the SoftFoot and describes the theoretical model which led to its final design. The proposed system has been experimentally tested and compared with two analogous conventional feet, a rigid one and a compliant one, with similar footprints and soles. The experimental validation focuses on the analysis of the standing performance, measured in terms of the equivalent support surface extension and the compensatory ankle angle, and the rejection of impulsive forces, which is important in events such as stepping on unforeseen obstacles. Results show that the SoftFoot has the largest equivalent support surface when standing on obstacles, and absorbs impulsive loads in a way almost as good as a compliant foot.

This paper presents a control scheme for force sensitive, gentle grasping with a Pisa/IIT anthropomorphic SoftHand equipped with a miniaturised version of the TacTip optical tactile sensor on all five fingertips. The tactile sensors provide high-resolution information about a grasp and how the fingers interact with held objects. We first describe a series of hardware developments for performing asynchronous sensor data acquisition and processing, resulting in a fast control loop sufficient for real-time grasp control. We then develop a novel grasp controller that uses tactile feedback from all five fingertip sensors simultaneously to gently and stably grasp 43 objects of varying geometry and stiffness, which is then applied to a human-to-robot handover task. These developments open the door to more advanced manipulation with underactuated hands via fast reflexive control using high-resolution tactile sensing.

This paper discusses how the disciplines of Design and Engineering are jointly addressing disability and somehow affecting its very interpretation. The discussion focuses on high-tech prostheses, where robotic devices substitute human body parts. The application of robotic technologies to prosthetics has a relatively long history. Nevertheless, only in the last decade have we witnessed applications reach the market and become available for a large base of users who were offered prostheses with superior motor and sensory performance. The process of bringing ever more advanced technologies to fruition by prosthetic users is fully ongoing today, with some promising solutions coming from robotics (such as, e.g. AI techniques or soft robotics materials) to be transferred to human use. In this transfer process, technology alone is insufficient to warrant success, and the need for a close collaboration between the Engineering domain and the Design disciplines is apparent. We address this point with specific reference to a case study, i.e. the transformation of an innovative but by-now established technology in the industrial robotics field (the “Pisa/IIT SoftHand”) into a prosthetic hand (the “SoftHand Pro”). Besides obvious technical considerations about size, connections, control, and so on, which can be addressed with a thorough technical revision of the design, what makes the profound difference between the two devices is that, as a prosthesis, the SoftHand is intended as a human body part, and not as an external tool. To reach its ultimate goals, the hand should become a part of the human user, with his body and mind. The empirical approach and tools of Designers afford the possibility to enrich the re-design process, considering the final user at the centre of the process, in a sort of renewed humanistic approach. The paper reflects this multidisciplinary approach and is structured as follows: the first part describes a cultural framework for the use of high-technology upper limb prostheses. This culture is defined through two significant relations (Users & Society; Users & Device). Inputs come from desk research conducted in different fields, ranging from Social Psychology to Medicine and Rehabilitation area. In this scenario, it is possible to extract design insights applicable to the design brief. The introduction of a robotic prosthetic hand (SoftHand Pro) and a related, single-user case study follow. The aim here is also to illustrate a process where engineering innovations are facilitated by tools from the Design field in the attempt to make the whole process coherently centred on users. Involved are all aspects, from material technology to the covering and finishing of the prosthetic device. The resulting, final prototype of the SoftHand Pro is finally presented.

Compliant actuation bestows robots with the ability to cope with unstructured environments, move with agility, and interact safely with humans at the expense of reduced tracking accuracy. The inclusion of dampening components aims to reduce oscillatory dynamics and partially restore precision without sacrificing the previously obtained characteristics. This paper introduces the concept and design of a novel damped compliant actuator suitable for building multi-degree of freedom systems. The proposed unit has a unique actuator topology that has never been seen before in the literature. The gearbox is used as a differential component, allowing the design of compact units without giving up safety and accuracy enhancements. We present and analyze the actuator's model and experimentally characterize the actuator prototype and the elastic and damping component.

Frequently, ground robots are hampered by debris and objects on the ground, and safely surpassing them is not always trivial. On the contrary, a robot capable of flying is intrinsically immune to such obstacles and, therefore, greatly enhances the possibility of inspecting and intervening in adverse surroundings for humans. This work introduces a novel teleoperated aerial platform for inspection and intervention in unstructured environments. The robot is composed of an aerial base, two arms, and a two-degrees-of-freedom head that consent the access of human operators in any workplace in total safety. The arms are designed with a joint structure of tendons and are held by elastic components. This composition considerably improves the robustness by inserting softness and redistributing the weights to lessen the actions on the drone. Moreover, the aerial platform employs two soft hands capable of adapting to the shape of the objects under grasp, increasing the manipulation performance. We presented the mechanical and control design, a gazebo simulation employed to test the controllers, and a physical structure for the experimental validation of the system. The system is available as Open-Source material.

The vast majority of state-of-the-art walking robots employ flat or ball feet for locomotion, presenting limitations while stepping on obstacles, slopes, or unstructured terrain. Moreover, traditional feet for quadrupeds lack sensing systems that are able to provide information about the environment and about the foot interaction with the surroundings. This further diminishes their value. Inspired by our previous work on soft feet for bipedal robots, we present the SoftFoot-Q, an articulated adaptive foot for quadrupeds. This device is conceived to be robust and able to overcome the limitations of currently employed feet. The core idea behind our adaptive foot design is first introduced and validated through a simplified mathematical formulation of the problem. Subsequently, we present the chosen mechanical implementation to attempt overcoming current limitations. The realized prototype of adaptive foot is integrated and tested on the compliantly actuated quadrupedal robot ANYmal together with an ROS-based real-time foot pose reconstruction software. Both extensive field tests and indoor experiments show noticeable performance improvements, in terms of reduced slippage of the robot, with respect to both flat and ball feet.

In this work, we report on how a sense of touch can be used to control an underactuated anthropomorphic robot hand, based on an integration that respects the hand’s mechanical functionality. Our focus is on integrating the sensorimotor control of the Pisa/IIT SoftHand, an anthropomorphic soft robot hand designed around the principle of adaptive synergies, with the BRL tactile fingertip (TacTip), a soft biomimetic optical tactile sensor. We consider: (i) closed-loop tactile control to establish a light contact on an unknown held object, based on the structural similarity of the tactile image; and (ii) controlling the estimated pose of a held object, using a convolutional neural network approach developed for other TacTip sensors. Accurate control was found for a range of hard and soft objects (to sub-millimetre accuracy and a few degrees). Overall, this gives a foundation to endow soft robotic hands with human-like touch, with implications for autonomous grasping, manipulation, human-robot interaction and prosthetics.

An approach toward intuitive and easy robot programming, consists to transfer skills from humans to machines, through demonstration. A vast literature exists on learning from multiple demonstrations. This paper, on the other hand, tackles the problem of providing all needed information to execute a certain task by resorting to one single demonstration - hence, a problem closer to programming than to learning. We use wearable consumer devices - but no keyboard nor coding - as programming tools, to let the programmer tele-operate the robot, which in turn records the most salient features and affordances from the object, environment, robot, and human. To enable this goal we combine off-the-shelf soft-articulated robotic components with the framework of Dynamic Movement Primitives, which we contribute to extend to generalize human trajectories and impedance regulation skills. This framework enables to teach robot quickly and in a intuitive way without coding. Experimental tests have been performed on a dual-arm system composed by two 7-dofs collaborative robots equipped with anthropomorphic end-effectors. Experiments show the functionality of the framework and verify the effectiveness of the impedance extension.

In this paper, we consider a problem of foothold selection for the quadrupedal robots equipped with compliant adaptive feet. Starting from a model of the foot we compute the quality of the potential footholds considering also kinematic constraints and collisions during evaluation. Since terrain assessment and constraints checking are computationally expensive we applied a Convolutional Neural Network (CNN) to evaluate the potential footholds on the elevation map. We propose an efficient strategy for data clustering and segmentation with CNN. The data for training the neural network is collected off-line but the inference works on-line when the robot walks on rough terrains and allows for efficient adaptation to the terrain and exploitation of the properties of the soft adaptive feet.

Restoring tactile sensation is essential to enable in-hand manipulation and the smooth, natural control of upper-limb prosthetic devices. Here we present a platform to contribute to that long-term vision, combining an anthropomorphic robot hand (QB SoftHand) with a neuromorphic optical tactile sensor (neuroTac). Neuromorphic sensors aim to produce efficient, spike-based representations of information for bio-inspired processing. The development of this 5-fingered, sensorized hardware platform is validated with a customized mount allowing manual control of the hand. The platform is demonstrated to succesfully identify 4 objects from the YCB object set, and accurately discriminate between 4 directions of shear during stable grasps. This platform could lead to wide-ranging developments in the areas of haptics, prosthetics and telerobotics.

Robotic teleoperation enables humans to safely complete exploratory procedures in remote locations for applications such as deep sea exploration or building assessments following natural disasters. Successful task completion requires meaningful dual arm robotic coordination and proper understanding of the environment. While these capabilities are inherent to humans via impedance regulation and haptic interactions, they can be challenging to achieve in telerobotic systems. Teleimpedance control has allowed impedance regulation in such applications, and bilateral teleoperation systems aim to restore haptic sensation to the operator, though often at the expense of stability or workspace size. Wearable haptic devices have the potential to apprise the operator of key forces during task completion while maintaining stability and transparency. In this paper, we evaluate the impact of wearable haptics for force feedback in teleimpedance control for dual-arm robotic teleoperation. Participants completed a peg-in-hole, box placement task, aiming to seat as many boxes as possible within the trial period. Experiments were conducted both transparent and opaque boxes. With the opaque box, participants achieved a higher number of successful placements with haptic feedback, and we saw higher mean interaction forces. Results suggest that the provision of wearable haptic feedback may increase confidence when visual cues are obscured.

This article presents the design of soft material robots with tunable damping properties. This study derives from the investigation of an under-actuated dynamic approach involving multi-chamber pneumatic systems. The co-design of the mechanical parameters (stiffness and damping) of the system along with the time profile of the input allows to obtain different behaviors using a reduced number of feeding line. In this work we analyze via simulations and experiments several approaches to tune the damping of soft robots. The most effective solution employs a layer of granular material immersed in viscous oil within the chamber wall. This method has been employed to realize bending actuators with a continuous deformation pattern. Finally, we show an application involving a two-fingered gripper fed by a single pneumatic line, which is able to perform pinch and power grasp.

The deployment of robotics in real-world scenarios, which may involve harsh and irregular physical interactions with the environment, such as those when robots operating in a disaster scenario, or the interactions that prosthetic devices may experience, demands hardware, which is physically resilient. The end-effectors, as the main media of interaction, are probably the parts at the highest risk. The capability of robotic hands to survive severe impacts is thus a necessity for the effective deployment of reliable robotic solutions in real-world tasks. Although, this robustness capability has been noted and discussed in the robotics community for long time, the literature does not provide a systematic study nor there is any proposal of standardized test or metric to evaluate hand resilience. In this work, inspired by the works of Charpy and Izod for the systematic definition of resilience and toughness of materials through impact tests, we consider extending the standard test to robot hands. We introduce a resilience evaluation framework, including a precisely defined experimental set-up and test procedure. As an example of application of the procedure, we apply it to experimentally characterize two robot hands, with a similar conceptual architecture but different size and material. From these tests we obtain several insights, including the observation that the dominant factor in hand resilience is their compliance and actuation principle, and that the use, under certain design conditions, of lightweight materials, such as plastic instead of aluminum, may not necessarily reduce the mechanical strength of the overall system.

One of the main research trends toward next-generation prostheses and bionic aids is to better replicate human motor behaviours and to improve the interconnection with the human sensory-motor architecture. One of the natural characteristics of the human arm of utmost importance in our interaction with the environment is our ability to vary the mechanical impedance of our joints by commanding the co-contraction of antagonist muscles. Integration in prostheses of such features is currently under studies. The introduction of physical variable impedance in the mechatronic structure of the devices could at the same time improve interaction and robustness and allow for more sophisticated controls with the goal of naturalness of motion. The system proposed in this paper is a variable stiffness elbow joint for upper limb prostheses that reproduces mechanical abilities of the human joint, in terms of performance, inherent compliance and natural behaviour. This variable stiffness mechanism can be actively controlled by the user, and by using an agonist-antagonistic configuration of proper elastic elements, its output functions are similar to the models of the human muscle. The design and mechanical implementation of the device are detailed in this document together with its experimental validation and characterisation.

Recently, the avenue of adaptable, soft robotic hands has opened simplified opportunities to grasp different items; however, the potential of soft end effectors (SEEs) is still largely unexplored, especially in human-robot interaction. In this paper, we propose, for the first time, a simple touch-based approach to endow a SEE with autonomous grasp sensory-motor primitives, in response to an item passed to the robot by a human (human-to-robot handover). We capitalize on human inspiration and minimalistic sensing, while hand adaptability is exploited to generalize grasp response to different objects. We consider the Pisa/IIT SoftHand (SH), an under-actuated soft anthropomorphic robotic hand, which is mounted on a robotic arm and equipped with Inertial Measurement Units (IMUs) on the fingertips. These sensors detect the accelerations arisen from contact with external items. In response to a contact, the hand pose and closure are planned for grasping, by executing arm motions with hand closure commands. We generate these motions from human wrist poses acquired from a human maneuvering the SH to grasp an object from a table. We obtained 86% of successful grasps, considering many objects passed to the SH in different manners. We also tested our techniques in preliminary experiments, where the robot moved to autonomously grasp objects from a surface. Results are positive and open interesting perspectives for soft robotic manipulation.

Grasp and manipulation is a complex task, deceivingly simple to accomplish for humans in everyday life, yet challenging to implement in a robotic hand. There is a trend in literature to use information obtained from studies on human grasp for the design and control of robotic manipulators. However, the effectiveness of such approach is dependent on the measurement tools that are available for use with human hands. While there are many sensing solutions that are designed for this purpose, obtaining a complete set of measurements of forces during grasp interaction is still challenging. In this work we aim to bridge this gap by introducing ExoSense, a passive hand exoskeleton. This device can provide position and orientation of the fingertips and, when integrated with the fingertip wearable force/torque sensing system ThimbleSense, a complete characterization of manipulation in terms of generalized forces and position of contacts on each fingertip in a completely wearable and unconstrained manner. After validating the device in terms of end-effector posture measurements and overall accuracy of grasp measurements, we report on a preliminary experiment aiming to show the potentialities of the system to study human internal grasp force variations and for neuroscientific investigation in general.

Thanks to the growing interest in soft robotics, hydropneumatics and inflatable system dynamics are attracting renewed attention from the scientific community. Typical fluidic systems are composed of several chambers and require a complex and bulky network of active components for their control. This paper presents a novel approach to fluidic actuation, which consists in the co-design of both the mechanical parameters of the system and of custom input signals, to enable the elicitation of different behaviors of the system with fewer control components. The principle is presented in theory and simulation and then experimentally validated through the application to a case study, an in-pipe inchworm-like robot. It is shown that it is possible to obtain forward and backward movements by modulating a unique input.

Despite the classic nature of the problem, trajectory tracking for soft robots, i.e., robots with compliant elements deliberately introduced in their design, still presents several challenges. One of these is to design controllers which can obtain sufficiently high performance while preserving the physical characteristics intrinsic to soft robots. Indeed, classic control schemes using high-gain feedback actions fundamentally alter the natural compliance of soft robots effectively stiffening them, thus de facto defeating their main design purpose. As an alternative approach, we consider here using a low-gain feedback, while exploiting feedforward components. In order to cope with the complexity and uncertainty of the dynamics, we adopt a decentralized, iteratively learned feedforward action, combined with a locally optimal feedback control. The relative authority of the feedback and feedforward control actions adapts with the degree of uncertainty of the learned component. The effectiveness of the method is experimentally verified on several robotic structures and working conditions, including unexpected interactions with the environment, where preservation of softness is critical for safety and robustness.

In recent years, a clear trend toward simplification emerged in the development of robotic hands. The use of soft robotic approaches has been a useful tool in this prospective, enabling complexity reduction by embodying part of grasping intelligence in the hand mechanical structure. Several hand prototypes designed according to such principles have accomplished good results in terms of grasping simplicity, robustness, and reliability. Among them, the Pisa/IIT SoftHand demonstrated the feasibility of a large variety of grasping tasks, by means of only one actuator and an opportunely designed tendon-driven differential mechanism. However, the use of a single degree of actuation prevents the execution of more complex tasks, like fine preshaping of fingers and in-hand manipulation. While possible in theory, simply doubling the Pisa/IIT SoftHand actuation system has several disadvantages, e.g., in terms of space and mechanical complexity. To overcome these limitations, we propose a novel design framework for tendon-driven mechanisms, in which the main idea is to turn transmission friction from a disturbance into a design tool. In this way, the degrees of actuation (DoAs) can be doubled with little additional complexity. By leveraging on this idea, we design a novel robotic hand, the Pisa/IIT SoftHand 2. We present here its design, modeling, control, and experimental validation. The hand demonstrates that by opportunely combining only two DoAs with hand softness, a large variety of grasping and manipulation tasks can be performed, only relying on the intelligence embodied in the mechanism. Examples include rotating objects with different shapes, opening a jar, and pouring coffee from a glass.

An effective robotic wrist represents a key enabling element in robotic manipulation, especially in prosthetics. In this paper, we propose an under-actuated wrist system, which is also adaptable and allows to implement different under-actuation schemes. Our approach leverages upon the idea of soft synergies — in particular the design method of adaptive synergies — as it derives from the field of robot hand design. First we introduce the design principle and its implementation and function in a configurable test bench prototype, which can be used to demonstrate the feasibility of our idea. Furthermore, we report on results from preliminary experiments with humans, aiming to identify the most probable wrist pose during the pre-grasp phase in activities of daily living. Based on these outcomes, we calibrate our wrist prototype accordingly and demonstrate its effectiveness to accomplish grasping and manipulation tasks.

Tele-operation in the presence of environmental constraints is a well-studied problem, where the difficulties of the transparency-stability trade-off have been elucidated by several important studies. While at the state-of-art, passivity-based stabilizers appear to provide the best insight and command over this problem, recent work by our group has proposed an alternative approach, which consists in measuring and replicating the master's limb endpoint impedance on the slave robot in real-time. Tele-impedance control offers advantages in certain conditions, e.g. where master-slave communications are low quality. However, force feedback remains necessary when visual feedback is impaired or transparency and telepresence in the remote environment is of major concern. In this paper, we propose a novel framework to achieve the Tele-Impedance with Force Feedback (TIFF) so as to have a seamless control scheme that subsumes the performance advantages of both, while still guaranteeing stability and transparency. Experimental results illustrate the potential of the proposed technique in addressing the drawbacks of the two concepts.

Sensing contact forces can be a key enabler for higher order dexterous manipulation in robotic hands. To sense the full range of contact pressure distribution would provide the best solution, but it is in practice unfeasible when considering very deformable and adaptable hands. This paper proposes an approach to estimate the contact forces acting on an under-actuated adaptable hand by combining the compliance model of the hand with the geometric configuration of the hand itself. This is done by introducing reasonable assumptions about the net contact force on each phalanx. The proposed method is introduced and experimentally validated on two fingers of the Pisa/IIT SoftHand.

In this work a novel synergy-based bilateral tele-manipulation strategy is introduced. The proposed algorithm has been primarily developed to remotely control the Pisa/IIT SoftHand (SH) using a 3-finger hand exoskeleton as master device. With a single actuator and a sensory system limited to a position encoder and a current sensor, the SH minimalist design promotes robustness but challenges traditional teleoperation strategies. To tackle this challenge, the concept of Cartesian-based hand synergies is introduced as a projection tool which maps the fingertip Cartesian space to the directions oriented along the grasp principal components. The unconstrained motion of the operator's hand is projected on this space to extract the SH's motor position reference. Conversely, the interaction force estimated at the robotic hand as a 1-dimensional force along the first synergy is projected to the 9D fingertip Cartesian space through an inverse projection. The resultant finger-individualized forces form a synergy based weighted representation of the grasping effort applied by the SH and are displayed to the operators fingertips using the force feedback hand exoskeleton. The system's ability to reflect the environment's impedance has been experimentally validated during a ball squeezing experiment. To assess the overall effectiveness of the proposed system as a manipulation interface, the SoftHand was mounted on the humanoid robot COMAN and the setup was subsequently enriched with a vision-based tracking system monitoring the operators wrist trajectory. Experimental results indicate that the proposed body-machine bilateral interface allows for the intuitive performance of stable grasps and transport of a large range of diversely shaped objects.

The deployment of robots to assist in environments hostile for humans during emergency scenarios require robots to demonstrate enhanced physical performance, that includes adequate power, adaptability and robustness to physical interactions and efficient operation. This work presents the design and development of the lower body of the new high performance humanoid WALK-MAN, a robot developed recently to assist in disaster response scenarios. The paper introduces the details of the WALK-MAN lower-body, highlighting the innovative design optimization features considered to maximize the leg performance. Starting from the general lower body specifications the objectives of the design and how they were addressed are introduced, including the selection of the leg kinematics, the arrangement of the actuators and their integration with the leg structure to maximize the range of motion, reduce the leg mass and inertia, and shape the leg mass distribution for better dynamic performance. Physical robustness is ensured with the integration of elastic transmission and impact energy absorbing covers. Experimental walking trials demonstrate the correct operation of the legs while executing a walking gait.

State of the art of hand prosthetics is divided between simple and reliable gripper-like systems and sophisticate hi-tech poly-articular hands which tend to be complex both in their design and for the patient to operate. In this paper, we introduce the idea of decoding different movement intentions of the patient using the dynamic frequency content of the control signals in a natural way. We move a step further showing how this idea can be embedded in the mechanics of an underactuated soft hand by using only passive damping components. In particular we devise a method to design the hand hardware to obtain a given desired motion. This method, that we call of the dynamic synergies, builds on the theory of linear descriptor systems, and is based on the division of the hand movement in a slow and a fast components. We use this method to evolve the design of the Pisa/IIT SoftHand in a prototype prosthesis which, while still having 19 degrees of freedom and just one motor, can move along two different synergistic directions of motion (and combinations of the two), to perform either a pinch or a power grasp. Preliminary experimental results are presented, demonstrating the effectiveness of the proposed design.

Rendering forces to the user is one of the main goals of haptic technology. While most force-feedback interfaces are robotic manipulators, attached to a fixed frame and designed to exert forces on the users while being moved, more recent haptic research introduced two novel important ideas. On one side, cutaneous stimulation aims at rendering haptic stimuli at the level of the skin, with a distributed, rather than, concentrated approach. On the other side, wearable haptics focuses on highly portable and mobile devices, which can be carried and worn by the user as the haptic equivalent of an mp3 player. This paper presents a light and simple wearable device (CUFF) for the distributed mechano-tactile stimulation of the user's arm skin with pressure and stretch cues, related to normal and tangential forces, respectively. The working principle and the mechanical and control implementation of the CUFF device are presented. Then, after a basic functional validation, a first application of the device is shown, where it is used to render the grasping force of a robotic hand (the Pisa/IIT SoftHand). Preliminary results show that the device is capable to deliver in a reliable manner grasping force information, thus eliciting a good softness discrimination in users and enhancing the overall grasping experience.

In this paper a model-free approach for damping control of Variable Stiffness Actuators is proposed. The idea is to take advantage of the possibility to change the stiffness of the actuators in controlling the damping. The problem of minimizing the terminal energy for a one degree of freedom spring-mass model with controlled stiffness is first considered. The optimal bang-bang control law uses a maximum stiffness when the link gets away from the desired position, i.e. the link velocity is decreasing, and a minimum one when the link is going towards it, i.e. the link velocity is increasing. Based on Lyapunov stability theorems the obtained law has been proved to be stable for a multi-DoF system. Finally, the proposed control law has been tested and validated through experimental tests.

Measuring contact forces applied by a hand to a grasped object is a necessary step to understand the mysteries that still hide in the unparalleled human grasping ability. Nevertheless, simultaneous collection of information about the position of contacts and about the magnitude and direction of forces is still an elusive task. In this paper we introduce a wearable device that addresses this problem, and can be used to measure generalized forces during grasping. By assembling two supports around a commercial 6-axis force/torque sensor we obtain a thimble that can be easily positioned on a fingertip. The device is used in conjunction with an active marker-based motion capture system to simultaneously obtain absolute position and orientation of the thimbles, without requiring any assumptions on the kinematics of the hand. Finally, using the contact centroid algorithm, introduced in [1], position of contact points during grasping are determined. This paper shows the design and implementation of the device, as well as some preliminary experimental validation.

A properly designed elastic actuation can increase the jumping height that a legged robot can reach. In this paper we compare the two most popular conceptual soft actuator designs, parallel elastic (PEA) and series elastic (SEA), in the task of maximizing the jumping height. Such task is translated into an optimal control problem. For a simplified version of the problem an analytical solution is provided, while a problem with more realistic constraints (e.g. the linear torque-speed motor characteristic is taken into account) is stated as a convex optimization problem and numerically solved. The results show that: (i) given the power of the motor there exists an optimal constant stiffness that maximizes the performance for both the SEA and the PEA; (ii) the optimal stiffness depends on the task terminal time, the inertial parameters of the system and the reduction ratio of the motor; (iii) in the condition considered the SEA behaves better than the PEA.

Since the introduction of the first prototypes of robotic end-effectors showing manipulation capabilities, much research focused on the design and control of robot hand and grippers. While many studies focus on enhancing the sensing capabilities and motion agility, a less explored topic is the engineering of the surfaces that enable the hand to contact the object. In this paper we present the prototype of the Velvet Fingers smart gripper, a novel concept of end-effector combining the simple mechanics and control of under-actuated devices together with high manipulation possibilities, usually offered only by dexterous robotic hands. This enhancement is obtained thanks to active surfaces, i.e. engineered contact surfaces able to emulate different levels of friction and to apply tangential thrusts to the contacted object. Through the paper particular attention is dedicated to the mechanical implementation, sense drive and control electronics of the device; some analysis on the control algorithms are reported. Finally, the capabilities of the prototype are showed through preliminary grasps and manipulation experiments.

In this paper, a novel synergy driven teleimpedance controller for the Pisa-IIT SoftHand is presented. Towards the development of an efficient, robust, and low-cost hand prothesis, the Pisa-IIT SoftHand is built on the motor control principle of synergies, through which the immense complexity of the hand is simplified into distinct motor patterns. As the SoftHand grasps, it follows a synergistic path with built-in flexibility to allow grasping of objects of various shapes using only a single motor. In this work, the hand grasping motion is regulated with an impedance controller which incorporates the user's postural and stiffness synergy profiles in realtime. In addition, a disturbance observer is realized which estimates the grasping contact force. The estimated force is then fedback to the user via a vibration motor. Grasp robustness and transparency improvements were evaluated on two healthy subjects while grasping different objects. Implementation of the proposed teleimpedance controller led to the execution of stable grasps by controlling the grasping forces, via modulation of hand compliance. In addition, utilization of the vibrotactile feedback resulted in reduced physical load on the user. While these results need to be validated with amputees, they provide evidence that a low-cost, robust hand employing hardware-based synergies is a viable alternative to traditional myoelectric prostheses.

Industrial grippers are often used for grasping, while in-hand re-orientation and positioning are dealt with by other means. Contact surface engineering has been recently proposed as a possible mean to introduce dexterity in simple grippers, as in the Velvet Fingers smart gripper, a novel concept of end-effector combining simple under-actuated mechanics and high manipulation possibilities, thanks to conveyors which are built in the finger pads. This paper undergoes the modeling and control of the active conveyors of the Velvet Fingers gripper which are rendered able to emulate different levels of friction and to apply tangential thrusts to the contacted objects. Through the paper particular attention is dedicated to the mechanical implementation, sense drive and control electronics of the device. The capabilities of the prototype are showed in some grasping and manipulation experiments.

Recent robotic research recognized the advantages that Variable Impedance Actuators would yield to a new generation of robots, rendering them adapt to many different tasks of everyday life.

This work presents an example of the application of passive impedance control of a variable stiffness manipulator, which shows the actual benefits of variable stiffness in rejecting disturbances without resorting to the closure of a high level feedback loop. In the experiment a 4-DOF manipulator arm, built with the VSA-CubeBot platform, is controlled to hold a pen and draw a circle on an uneven surface. The control is designed calculating joint and stiffness trajectories with a Cartesian approach to the problem, thus designing the optimal workspace stiffness at first. Then, the joint stiffness yielding the closest workspace stiffness is searched for. Experimental results are reported, which agree with the theoretical outcomes, showing that the sub-optimal joints stiffness settings allow the arm to follow the circular trajectory on the uneven surface at best.

To match the richness and complexity of the sensory and motor functionalities of a human hand with a robust and economically reasonable robotic device remains one of the hardest challenges in the field. Previous work has explored the possibility to exploit insight from neuroscientific results on postural correlation patterns (synergies) taming the sensorimotor complexity of hands. The postural synergy model has been recently extended to account for grasp force control through a model of “soft synergies” which incorporate hand compliance. In this paper we propose a first translation of such principles in the design of a robot hand. It so turns out that the implementation of the soft synergy model in an effective design is not obvious. The solution proposed in this paper rests on ideas coming from under-actuated hand design. We give a synthesis method to realize a desired set of soft synergies through the principled design of adaptive under-actuated mechanisms, which we call the method of adaptive synergies. This approach leads to the design and implementation of a prototype modular hand capable of accommodating an arbitrary number of synergies. The effectiveness of the design is shown in grasping simulations and experiments.

The design of grasping and manipulation systems is one of the most investigated topics in recent robotic and automation engineering. It is a process that has to take into account many development possibilities and to face different trade offs, as that between application possibilities and design complexity. In this work we present the design of a novel end-effector that merges the essential mechanics and control simplicity of underactuated devices, together with the high levels of manipulability usually featured in dexterous robotic hands. To obtain this enhancement, the proposed gripper considers the possibility offered by active surfaces, i.e. engineered contact surfaces able to simulate different levels of friction and to apply tangential thrust to the contacted object. The actual dexterity enhancement is evaluated by an analytical manipulability analysis and some examples of in hand manipulations and grasps are taken into account. A mechanical solution is presented, which implements the proposed idea through the adoption of one DoF active surfaces mounted on the fingers. The proposed solution presents a manipulability index one order of magnitude higher than common grippers.

Most of today's robots have rigid structures and actuators requiring complex software control algorithms and sophisticated sensor systems in order to behave in a compliant and safe way adapted to contact with unknown environments and humans. By studying and constructing variable impedance actuators and their control, we contribute to the development of actuation units which can match the intrinsic safety, motion performance and energy efficiency of biological systems and in particular the human. As such, this may lead to a new generation of robots that can co-exist and co-operate with people and get closer to the human manipulation and locomotion performance than is possible with current robots.

We propose a prototype of a Variable Stiffness Actuator (VSA) conceived with low cost as its first goal. This approach was scarcely covered in past literature. Many recent works introduced a large number of actuators with adjustable stiffness, optimized for a wide set of applications. They cover a broad range of design possibilities, but their availability is still limited to small quantities. This work presents the design and implementation of a modular servo-VSA multi-unit system, called VSA-CubeBot. It offers a customizable platform for the realization and test of variable stiffness robotic structures with many degrees of freedom. We present solutions relative to the variable stiffness mechanism, embedded electronics, mechanical and electrical interconnections. Characteristics, both theoretic and experimental, of the single actuator are reported and, finally, five units are interconnected to form a single arm, to give an example of the many possible applications of this modular VSA actuation unit.

This paper presents a systematic enumeration and performance analysis of Variable Stiffness Actuators (VSAs). VSAs are becoming more and more popular in robotics, and many different prototypes have been recently proposed and built in the research community. In comparison with conventional geared motors, actuators with variable stiffness introduce the need for new specifications, requirements, and performance criteria, concerning e.g. the range of achievable stiffness, and the response time to stiffness reference changes. On the other hand, the mechanical construction of VSAs is also more complex. To address the problem of harnessing the increased complexity of VSA design, we consider in this article the enumeration of all possible arrangements of two prime movers (elementary motors), two harmonic-drive gears, the output shaft, and the interconnections (either rigid or elastic) between these elements. We propose an automated algorithm to search the large combinatorics of such enumeration, and present a reduced number of feasible basic designs which accomplish the objectives of VS actuation. Furthermore, we propose a quasi-static model of VS actuators which can be used for an analysis of their performance and we conclude by presenting some preliminary characteristics of one of the selected designs.

This paper focuses on casting manipulation and presents an innovative mechanism that allows objects placed in a three-dimensional space to be reached with a relatively small robot. Casting manipulation is a technique by which a robotic end-effector is thrown and its ballistic flight is controlled through a tether cable so as to reach a target object. Previous work presented a solution that is viable only when the position of the target object is perfectly known or aligned with the throwing plane. Our work extends the technique by use of a novel mechanical design of the arm, and a suitable control scheme for the flight of the end-effector, which makes it applicable for objects placed at generic positions in a three-dimensional environment. Effectiveness of the casting robot was shown during the first ESA Lunar Robotics Challenge, where our team came in the second place.

This paper presents design, implementation and performance of a new Variable Stiffness Actuator (VSA) based on Harmonic Drives (VSA-HD), which is an improvement over past work reported in. While previous prototypes have been developed to demonstrate the effectiveness of the variable stiffness actuation principle and the possibility to develop a compact and reliable actuator, the VSA-HD has been obtained by exploring the performance of the enumeration of all VSA made out a basic components set (i.e. two prime movers, two harmonic-drive gears, and the output shaft) and all the feasible interconnections between them as presented in. Along this enumeration the VSA-HD conceptual layout has been selected as being good trade-off between mechanical complexity and overall performance. This paper discusses in depth the actuator mechanical layout, highlighting the main characteristics of the new design. A model for the actuator is introduced and validated by experimental results.

This paper describes the design and implementation of DAVID, a lunar vehicle developed for the European Space Agency (ESA) Lunar Robotics Challenge, presenting severe terrain negotiation and sample acquisition challenges. We discuss in some detail two of the main innovative aspects of our entry to the challenge, i.e. the locomotion system and the sample acquisition system. Motivated by the challenge specifications, a range of different locomotion systems were considered, among which we chose a simple, rugged and effective wheeled system. We provide an account of the choice of five different types of wheels, which were designed, analyzed and experimentally tested in conditions similar to the challenge. The system eventually turned out to be very effective in negotiating 89% slopes of volcanic terrain on the challenge site, Mount Teide in Tenerife. To reduce the distance to be traveled on the difficult terrain and avoid risks in reaching the lowest parts of a crater, the vehicle was endowed with an innovative sample acquisition system, i.e. a casting manipulator. Casting manipulation is a technique in which the end-effector is thrown, the sample material is acquired, and the end-effector is retrieved using a light tether that acts as a "fishing line". The casting manipulator developed for DAVID uses an innovative sling-like technique, capable to obtain longer and more precise casts than previous oscillating versions. The analysis and experimental verification of DAVID's robot sling are reported, demonstrating its effectiveness. Finally, we give a brief account of the outcomes of the ESA Lunar Robotics Challenge, where our team came in second over other 8 teams that passed the final qualification phase.