This paper explores the challenge of optimal routing for a mobile robot navigating a dynamic and shared human environment. The primary goal is to minimize the risk of performance degradation during motion, such as delays in completing tasks due to the need for safe or acceptable human robot encounters. The problem is formulated as a graph whose edge costs become progressively known only as the robot moves through the environment. We model this problem as a Markov Decision Process (MDP), enabling an offline evaluation of the expected cost of alternative routes based on statistical information about human spatial distributions and possible observations at each intersection. This compact state representation scales linearly with the number of intersections in the map. Since the memoryless property of the MDP may induce loops during online execution, we compute an offline policy and introduce an online policy adaptation mechanism to prevent cyclic behaviors. Exten sive simulations across environments of different complexity, and using data collected from real-world experiments, demonstrate that our approach outperforms reactive and advanced state-of the-art planners in terms of either performance or scalability.

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.

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.

Due to their fast and efficient locomotion, two-wheeled humanoids are fascinating systems with the potential to be involved in many application domains, including healthcare, manufacturing, and many others. However, these robots constitute a challenging case of study for control purposes due to the two-wheeled inverted pendulum dynamics that characterizes their mobility and support, as it is underactuated and unstable. In this article, we propose a novel whole-body control approach to stabilize two-wheeled humanoids. To tackle the control problem of their forward motion and pitch equilibrium, leveraging on the observation that such systems are usually characterized by a faster and a slower dynamics (being the pitch angle faster and the forward displacement slower), we design a composite whole-body control that combines two computed-torque control loops to stabilize both dynamics to the desired trajectories. The control approach is introduced and its derivation is described for the simpler case of a two-wheeled inverted pendulum first, and for a whole two-wheeled humanoid after. To prove its validity, the control approach is tested experimentally on the two-wheeled humanoid robot Alter-Ego. The robot proves to be able to perform complicated interaction tasks, including opening a door, grasping a heavy object, and resisting to external dynamic disturbances.

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.

Characterizing the risk of operations is a fundamental requirement in robotics, and a crucial ingredient of safe planning. The problem is multifaceted, with multiple definitions arising in the vast recent literature fitting different application scenarios and leading to different computational approaches. A basic element shared by most frameworks is the definition and evaluation of the probability of collision for a mobile object in an environment with obstacles. We observe that, even in basic cases, different interpretations are possible. This article proposes an index we call “Risk Density,” which offers a theoretical link between conceptually distant assumptions about the interplay of single collision events along a continuous path. We show how this index can be used to approximate the collision probability in the case where the robot evolves along a nominal continuous curve from random initial conditions. Indeed, under this hypothesis the proposed approximation outperforms some well-established methods either in accuracy or computational cost.

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 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 many real-world manipulation problems, the constraints imposed by the environment on an object are tight. In these cases, most state-of-the-art planners struggle to fit satisfactorily in low dimensional sub-manifolds, while still ensuring geometric and force feasibility. On the other hand, humans are at ease with such situations and indeed exploit constraints to manipulate objects proficiently.To face this challenge, we propose to merge state-of-art randomized grasp planning methods with model-based grasp analysis. We use the partial form-closure analysis framework to find the geometrically feasible motions of the object. Then, to ensure that the desired motions are physically realizable by the robot, we resort to an extension of the force-closure analysis framework accounting also for dynamic friction. We use these instruments to construct a random tree in a simplified planning space containing only object-robot configurations that are reachable through effectively applicable contact forces. The algorithm, validated in simulation and in preliminary experiments with a collaborative robot, features the ability to compute solutions for heavily constrained real-world manipulation problems.

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.

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.

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.

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.

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.

Safe physical human-robot interaction, conservation of energy, and adaptability are the main robotic applications that prompted the development of a number of variable stiffness actuators (VSAs). Implemented in a variety of ways, they use various technologies and feature the most diverse mechanical solutions, all of which share a fundamentally unavoidable nonlinear behavior. The control schemes proposed for these actuators typically aim at independent control of the position of the link and its stiffness. Although effective feedback control schemes using position and force sensors are commonplace in robotics, control of stiffness is at present completely open loop: The stiffness is inferred from the mathematical model of the actuator. We consider here the problem of estimating the nonlinear stiffness of VSA in agonistic-antagonistic configuration. We propose an algorithm based on modulating functions that allow us to avoid the need for numerical derivative and for which the tuning is then very simple. An analysis of the error demonstrates the convergence. Simulations are provided, and the algorithm is validated on experimental data.

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.

We consider the problem of estimating the time-varying stiffness in real-time of a Variable Stiffness Actuator in an agonistic-antagonistic configuration. The estimation of the stiffness is done in two steps. First, we use operational calculus which provides a relation between the positions/velocities of the motors and the link, the torques of the motors and the stiffness. Second, we combine the obtained relation with a polynomial approximation of the stiffness and a recursive least square algorithm to fit the data. Simulations and experimental results are provided and demonstrate the effectiveness of the proposed approach.

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.

We consider the problem of estimating non-linear time-varying stiffness of a mechanical system based only on force and position measurements. A recent work presented a non-parametric stiffness observer, which converges to within an Uniformly Ultimately Bounded neighborhood of the real stiffness value. The method provides excellent results for applications where the system is persistently excited. In this paper, we provide a parametric identification method that complements the previous solution in that it can provide, after a sufficiently long learning period, a complete model of the nonlinear stiffness, which can be applied henceforth even in the absence of excitation. Convergence conditions for the proposed method are discussed. Simulation and experimental results are provided, illustrating the performance of the proposed algorithm.

This paper focuses on the estimation of the impedance for a Variable Impedance Actuator (VIA) through torque and position measurements. Despite the recent development of several VIA, impedance control is not yet implemented in closed loop because of the difficulty of obtaining in real-time measurements of time-varying impedance. The estimation algorithm is proposed as an alternative approach to the standard procedures of impedance identification, to robustly tolerate the variability of the mechanical stiffness due, for example, to model uncertainties. The impedance estimator is therefore implemented on the Actuator with Adjustable Stiffness (AwAS). The effectiveness of the proposed estimator is proved through simulation and experimental results.

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.

This paper presents design and performance of a novel joint based actuator for a robot run by variable stiffness actuation, meant for systems physically interacting with humans. This new actuator prototype (VSA-II) is developed as an improvement over our previously developed one reported in [9], where an optimal mechanical-control co-design principle established in [7] is followed as well. While the first version was built in a way to demonstrate effectiveness of variable impedance actuation (VIA), it had limitations in torque capacities, life cycle and implementability in a real robot. VSA-II overcomes the problem of implementability with higher capacities and robustness in design for longer life. The paper discusses design and stiffness behaviour of VSA-II in theory and experiments. A comparison of stiffness characteristics between the two actuator is discussed, highlighting the advantages of the new design. A simple, but effective PD scheme is employed to independently control joint-stiffness and joint-position of a 1-link arm. Finally, results from performed impact tests of 1- link arm are reported, showing the effectiveness of stiffness variation in controlling value of a safety metric.