Wearable robots, such as exoskeletons and assistive gloves, must operate in close physical interaction with the human body, where safety, comfort, adaptability, and biomechanical compatibility are critical requirements. Simulation plays a central role in the design, analysis, and optimization of wearable robotic devices, enabling a systematic and human-centered development process. Simulation frameworks provide essential tools to model the complex coupling between human biomechanics, device mechanics, actuation systems, and control strategies. By integrating musculoskeletal models, multibody dynamics, and compliant actuation representations, simulation allows designers to evaluate device performance across a wide range of users, tasks, and operating conditions before physical prototyping. This approach supports the exploration of design trade-offs, such as assistance effectiveness versus user comfort, or actuator placement versus wearability. Furthermore, simulation enables the assessment of interaction forces, joint loading, and energy exchange, contributing to safer and more ergonomic solutions. In wearable robotics research inspired by human-in-the-loop principles, simulation is also important in developing and validating control strategies, including assist-as-needed paradigms and adaptive controllers that respond to user intent and variability.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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