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The purpose of this work is to develop a methodology to improve human-robot collaboration for robot-aided dental implant placement. In this study, a human-robotic implant system (HRIS) is designed according to a hand-guiding control to increase the accuracy and stability of osteotomy drilling based on the surgeon's decision, and robot motion during the implant placement. The proposed method is able to guide the surgeon's hand according to the pose of the desired placement. To guide and modify the pose of the surgeon's hand, the virtual fixture method is used as the main control approach. To verify the performance of the introduced method, the KUKA MED robot is used to perform the dental implant placement using the presented approach on a phantom head with a 3D jaw bone model. Additionally, the results between free-hand drilling and HRIS controlled drilling according to the apical center and head center of the implant placement are compared to evaluate the performance of the introduced method.

Depalletizing robotic systems are commonly de- ployed to automatize and speed up parts of logistic processes. De- spite this, the necessity to adapt the preexisting logistic processes to the automatic systems often impairs the application of such robotic solutions to small business realities like supermarkets. Integrating a robotic system into the supermarket depalletizing process demands a high level of autonomy, based on strong perceptive, executive and gripping capabilities. This abstract describes an integrated robotic depalletizing system designed to be easily deployed into supermarket logistic processes. The system is described along with its main components, showing how the proposed framework performs in a real supermarket scenario.

Handling non-rigid objects using robot hands necessities a framework that does not only incorporate human-level dexterity and cognition but also the multi-sensory information and system dynamics for robust and fine interactions. In this research, our previously developed kernelized synergies framework, inspired from human behaviour on reusing same subspace for grasping and manipulation, is augmented with visuo-tactile perception for autonomous and flexible adaptation to unknown objects. To detect objects and estimate their poses, a simplified visual pipeline using RANSAC algorithm with Euclidean clustering and SVM classifier is exploited. To modulate interaction efforts while grasping and manipulating non-rigid objects, the tactile feedback using T40S shokac chip sensor, generating 3D force information, is incorporated. Moreover, different kernel functions are examined in the kernelized synergies framework, to evaluate its performance and potential against task reproducibility, execution, generalization and synergistic re-usability. Experiments performed with robot arm-hand system validates the capability and usability of upgraded framework on stably grasping and dexterously manipulating the non-rigid objects., Comment: IEEE ICRA 2022 (under review)

In robot-aided surgery, during the execution of typical bimanual procedures, surgical tools can collide and create serious damage to the robot or tissues. The da Vinci robot is one of the most widespread robotic system dedicated to minimally invasive surgery. Although the procedures performed by da Vincilike surgical robots are teleoperated, potential collisions between surgical tools are a very sensitive issue declared by surgeons. Shared control techniques based on Virtual Fixtures (VF) can be an effective way to help the surgeon prevent tools collision. This paper presents a surgical tools collision avoidance method that uses Forbidden Region Virtual Fixtures. To ensure the correct definition of the VF, a marker-less tool tracking method and the Extended Kalman Filter (EKF) are used for tool pose estimation., https://youtu.be/NAxAT7NRHKE https://www.youtube.com/watch?v=N7wjQrGYHdY

In this paper it is shown how a 2-DoF inherently force balanced spatial deployable Butterfly Linkage is found consisting of four entangled similar Bennett linkages moving synchronously and with the common center of mass in the central joint. This linkage is derived from the Grand 4R Four-Bar Based Inherently Balanced Linkage Architecture by selecting a planar linkage with four entangled similar 4R four-bar linkages to which the Bennett conditions are applied. The inherent balance conditions are calculated, which are independent of the Bennett angles, and a CAD-model of the linkage is presented.

Pruning is the art of cutting unwanted and unhealthy plant branches and is one of the difficult tasks in the field robotics. It becomes even more complex when the plant branches are moving. Moreover, the reproducibility of robot pruning skills is another challenge to deal with due to the heterogeneous nature of vines in the vineyard. This research proposes a multi-modal framework to deal with the dynamic vines with the aim of sim2real skill transfer. The 3D models of vines are constructed in blender engine and rendered in simulated environment as a need for training the robot. The Natural Admittance Controller (NAC) is applied to deal with the dynamics of vines. It uses force feedback and compensates the friction effects while maintaining the passivity of system. The faster R-CNN is used to detect the spurs on the vines and then statistical pattern recognition algorithm using K-means clustering is applied to find the effective pruning points. The proposed framework is tested in simulated and real environments., Comment: Under Review at SPAR

Manipulation in contrast to grasping is a trajectorial task that needs to use dexterous hands. Improving the dexterity of robot hands, increases the controller complexity and thus requires to use the concept of postural synergies. Inspired from postural synergies, this research proposes a new framework called kernelized synergies that focuses on the re-usability of the same subspace for precision grasping and dexterous manipulation. In this work, the computed subspace of postural synergies; parameterized by probabilistic movement primitives, is treated with kernel to preserve its grasping and manipulation characteristics and allows its reuse for new objects. The grasp stability of the proposed framework is assessed with a force closure quality index. For performance evaluation, the proposed framework is tested on two different simulated robot hand models using the Syngrasp toolbox and experimentally, four complex grasping and manipulation tasks are performed and reported. The results confirm the hand agnostic approach of the proposed framework and its generalization to distinct objects irrespective of their shape and size.

One of the main challenges of simulating virtual objects by haptic devices is instability, especially in simulating stiff objects. In this paper, a stability criterion for a haptic device is derived using Lyapunov approach. The haptic device is modeled as a mass and viscous friction, which has to simulate the touching a virtual environment (VE) with specified stiffness and damping. Dynamic equations and state-space equations are derived with assumption of small values of sampling time, time delay and virtual damping. A Lyapunov function is proposed, consisting of summation of kinetic and potential energy of the system, plus two unknown terms. Each one of these two unknown terms is a function of one system states (i.e. position and velocity). These two functions are determined so that, from one side the Lyapunov function be positive definite, and from the other side the stability criterion is reached with putting time derivation of the Lyapunov function negative. The stability condition determined by this method is a linear criterion between maximum permissible virtual stiffness, virtual damping of the VE, physical damping of the haptic device, sampling time and time delay, and is consistent with the results of previous researches with linear methods. The importance of the presented analysis in this paper is that this method can be extended by adding new terms to the Lyapunov function, to remove some limitations and to take into account nonlinear effects. Presented criterion and its results are verified by experiments on KUKA robot.

2nd Edition

Redundancy offers a potential over nonredundancy in robot design and control in terms of greater motion/force manipulability. The solution to the kinematic control problem is crucial for an effective use of redundancy. The redundant degrees-of-freedom's can be used to meet additional motion/force constraints, such as dexterity, task compatibility, obstacle avoidance, and limited joint range. The augmented task space approach is adopted and a recently established computational method to solve the constrained inverse kinematic problem is proposed. A case study for a snake-like robot operating in a constrained environment is developed and simulation results are included.

Kinematic control of robot manipulators requires the computation of reference trajectories for the joint servos, through an inverse kinematics, to execute a given end-effector trajectory. A key point is concerned with end-effector orientation description which may lead to the occurrence of the so-called representation singularities. To overcome this drawback, in this paper a closed-loop inverse kinematics algorithm is presented where the unit quaternion is conveniently adopted in lieu of the Euler angles. The implementation on an industrial robot manipulator in a number of case studies is described.

Despite technological progress in instrumental diagnostic investigations of the last decade, prostate cancer remains one of the most frequent malignant tumors and the second leading cause of cancer death among men. Although prostate biopsy remains the reference among all diagnosis procedures, it still exposes patients to the risk of developing complications. In this paper, the authors present a novel robotic system for prostate cancer diagnosis aimed at improving the current diagnostic procedures and reducing their undesired effects. The purpose of this work is to validate the proposed methodology by considering experimental analysis on both phantom and ex-vivo prostate tissues.

The sliding primitive is a ubiquitous nonprehensile manipulation task, generally performed by mechanical systems represented by underactuated nonlinear models. A literature review of the recent works dealing with this task is first introduced. Then, a particular nonprehensile manipulation task that has arisen in the framework of the RoDyMan project, i.e., a pizza and peel mechanical system, is addressed. A more in-depth study is presented for this system, including modelling, control, and stability analysis. Finally, a discussion on the current achievements and some directions for future work is provided. This chapter is based on the work presented in [1].

This chapter reviews the problem of nonholonomic rolling in nonprehen- sile manipulation tasks through two challenging and illustrative examples: the robotic hula-hoop and the ballbot system. The hula-hoop consists of an actuated stick and an unactuated hoop. First, the corresponding kinematic model is derived. Second, the dynamic model is derived through the Lagrange-D’Alembert equations. Then a control strategy is designed to rotate the hoop at some desired constant speed whereas positioning it over a desired point on the stick surface. A stability analysis, which guarantees ultimate boundedness of all signals of interest, is carried out. The ball-bot is an underactuated and nonholonomic constrained mobile robot whose upward equilibrium point must be stabilised by active controls. Coordinate-invariant equations of motion are derived for the ballbot. The linearised equations of motion are then derived, followed by the detailed controllability analysis. Excluding the rotary degree of freedom of the ball in the inertial vertical direction, the linear system turns out to be controllable. It follows that the nonlinear system is locally controllable, and a proportional-derivative type controller is designed to locally exponentially stabilise the upward equilibrium point and the translation of the ball. Numerical simulations for these two examples illustrate the effectiveness of the proposed methods. This chapter is based on the works presented in [1–4].

Nowadays haptic devices have lots of applications in virtual reality systems. While using a haptic device, one of the main requirements is the stable behavior of the system. An unstable behavior of a haptic device may damage itself and even may hurt its operator. Stability of haptic devices in the presence of inevitable time delay in addition to a suitable zero-order hold is studied in the presented paper, using two different methods. Both presented methods are based on Lyapunov-Krazuvskii functional. In the first method, a model transform is performed to determine the stability boundary, while the second approach is based on Free Weighing Matrices (FWMs). Delay-dependent stability criteria are determined by solving Linear Matrix Inequalities (LMIs). Results of these two methods are compared with each other and verified by simulations as well as experiments on a KUKA Light Weight Robot 4 (LWR4). It is concluded that using free weighing matrices leads to more unknown parameters and needs more calculation, but its results are less conservative.

This paper presents a new procedure to design a control law using the classical interconnection and damping assignment technique within the passivity-based port-Hamiltonian framework. The sought goal is to reduce the complexity of solving the so-called matching equations. The proposed approach is applied to two case studies of planar rolling nonprehensile manipulation, namely, the ball-and-beam and the eccentric disk-on-disk. The performance of the resulting controllers is illustrated through both simulations and experimental results, showing the applicability of the design in a real setup.

Humans in contrast to robots are excellent in performing fine manipulation tasks owing to their remarkable dexterity and sensorimotor organization. Enabling robots to acquire such capabilities, necessitates a framework that not only replicates the human behaviour but also integrates the multi-sensory information for autonomous object interaction. To address such limitations, this research proposes to augment the previously developed kernelized synergies framework with visual perception to automatically adapt to the unknown objects. The kernelized synergies, inspired from humans, retain the same reduced subspace for object grasping and manipulation. To detect object in the scene, a simplified perception pipeline is used that leverages the RANSAC algorithm with Euclidean clustering and SVM for object segmentation and recognition respectively. Further, the comparative analysis of kernelized synergies with other state of art approaches is made to confirm their flexibility and effectiveness on the robotic manipulation tasks. The experiments conducted on the robot hand confirm the robustness of modified kernelized synergies framework against the uncertainties related to the perception of environment.

In this paper, an intelligent variable impedance control combined with a fuzzy gain dynamic surface is proposed to improve the interaction of the robot manipulator with an unknown varied environment. The parameters of the proposed variable impedance are adapted by optimization an introduced cost function using a recurrent fuzzy wavelet network. The stability conditions for the varying inertial, stiffness and damping are presented to guarantee the stability of the variable impedance. Additionally, a fuzzy dynamic surface method is developed to tune the gains of the dynamic surface as a robust controller. The proposed fuzzy gain dynamic surface is used to force the end-effector of the manipulator to track the desired impedance profile in the presence of large disturbances. Using Lyapunov's method, the stability of the mentioned closed-loop system is proved. Finally, by using a designed simulator for IRB120 (ABB) robot, several simulations are carried out to verify the performance of the proposed method for the execution of various tasks in an unknown varied environment in the presence of large disturbances.

Mathematical modeling of hybrid soft robots is complicated by the description of the complex shape that they undergone when subject to actuation and external loads. It might be noticed that several approaches have been used so far in robotics, and the problem is not yet fully solved. This short paper aims at presenting an overview of modeling and simulation approaches for soft robots based on finite element methods. Benefits and perspectives of future directions are also discussed.

During robot-aided surgical interventions, the surgeon can be benefitted from the application of virtual fixtures (VFs). Though very effective, this technique is very often not practicable in unstructured surgical environments. In order to comply with the environmental deformation, both the VF geometry and the constraint enforcement parameters need to be online defined/adapted. This letter proposes a strategy for an effective use of VF assistance in minimally invasive robotic surgical tasks. An online VF generation technique based on the interaction force measurements is presented. Pose and geometry adaptations of the VF are considered. Passivity of the overall system is guaranteed by using energy tanks passivity-based control. The proposed method is validated through experiments on the da Vinci Research Kit.

In laparoscopic minimally invasive robotic surgery, a teleoperated robot is interposed between the patient and the surgeon. Despite the robot aid, the manipulation capabilities of surgical instruments are far from those of the human hand. In this letter, we want to make a step forward toward robotic solutions that can improve manipulation capabilities of the surgical instruments. A new concept of needle-driver tool is presented, which takes inspiration from the human hand model. The idea is to modify a standard laparoscopic tool by introducing an additional degree of freedom, which allows in-hand reorientation of the suturing needle. A 3D printed prototype has been built to validate the tool design. The improved manipulation capabilities have been assessed quantitatively by evaluating a weighted dexterity index along a single stitch trajectory. Moreover, a comparison between our tool and a standard needle driver has been done in terms of time required for the execution of a complete suturing sequence.

A mechanical system consisting of a hoop and a pole is considered, for which the corresponding dynamic model represents an underactuated system subject to second-order nonholonomic constraints. The pursued goal is to simultaneously track a trajectory in the unactuated coordinates and to stabilize the actuated ones. For the model under consideration, the well-known noncollocated partial feedback linearization algorithm fails since the corresponding zero dynamics is unstable. In this work, we show that the actuated coordinates, i.e., the pole can be stabilized by exploiting the null space of the coupling inertia matrix without affecting the performance in the underactuated coordinates tracking. We present a formal mathematical analysis, which guarantees ultimate boundedness of all coordinates. Performed simulations bolster the proposed approach.

The contact kinematics of a robotic hoop and a pole system is obtained by using the Montana’s equations, considering the case of contact without slipping. The resulting kinematic model is completely nonholonomic. After some mild assumptions, a set of Pfaffian constraints is established. Then, a dynamic model of the system is developed by employing the Lagrange– d’Alembert formulation. This dynamic model, which represents an underactuated mechanical system, is later used to design a controller which does not need velocity measurements. The proposed method, and its robustness against model uncertainties, is validated through numeric simulations.

A Variable Impedance Actuator (VIA) is an ac- tuator with dedicated elements that decouple the motor inertia form the link inertia in a compli- ant and damped manner. The compliance and/or damping can be varied actively in order to adapt the natural robot behavior according to the de- sired task.

The novel underactuated design of the PRISMA HAND I and its multimodal control based on integrated electromyographic signals and voice commands is presented. Due to limitations of EMG sensors and residual physiological signals of amputees, a smart solution utilizing a voice recognition module has been integrated into the EMG control to realize advanced intuitive commands and easy connection with the arm. Inspired by neuroscience studies on the human hand, two motor synergies have been implemented. The thumb adduction/abduction independent motion allows in-hand manipulation. The transmission system is based on whiffletree and pulleys for motion differentiation and on antagonistic elastic tendons. Using EMG and voice commands, the motors are moved together in a certain number of combination suitably and easily programmed using Arduino electronic prototyping. The use of a current sensor allows controlling the strength of the grasp to handle also fragile objects. The contributions of this work are: the bio-inspired design of kinematics and motion couplings by means of two motor synergies, the simple and efficient control interface allowing easy connection to the arm and intuitive use, finally, the cost reduction using economic hardware and mechanical components while preserving performance.

This chapter aims the broadcasting of the results achieved by the RoDyMan project about the task planning manipulation of deformable objects, and the nonprehensile manipulation control. The final demonstrator of the project is a pizza-making process. After an introduction to the general topic of nonprehensile manipulation, the mechatronic design and the high-level software architecture are described. Then, the smoothed particle hydrodynamic formulation is briefly introduced, along with the description of a detection method for a deformable object. The task planning for stretching a modelling clay, emulating the pizza dough, is sketched. After, the problematic control objective is split into several nonprehensile motion primitives: holonomic and nonholonomic rolling, friction-induced manipulation, and tossing are the described primitives. This chapter highlights the achievements reached so far by the project, and pave the way towards future research directions.

This letter addresses the task of stabilizing a wheeled unmanned aerial vehicle on a pipe, which is an emerging application in oil and gas facilities for nondestructive measurements. After the derivation of the dynamic model of the system, a discrete-time nonlinear model predictive controller is designed over a finite horizon. The analysis of the asymptotic stability of the designed controller is carried out. Numerical tests show the performance and the robustness of the proposed solution.

A nonprehensile manipulation system consisting of a dexterous plate (e.g., a peel) which is intended to induce a rotating movement on a disk (e.g., a pizza) is studied. A dynamic model based on the Euler-Lagrange equations is first derived. Then, a controllability analysis of this model is carried out, which shows some intrinsic limitations of the proposed system. Later, a closed-loop control strategy is proposed to induce the desired rotating speed in the disk, while maintaining the position of both the disk and the plate as close to zero as possible. A stability analysis is performed to show the boundedness of all the states, the oscillatory response of all of them, and the maximum amplitude of these oscillations. A numerical simulation is employed to verify the proposed controller and the predicted behavior found in the stability analysis.

Tissue elasticity is universally recognized as a diagnostic and prognostic biomarker for prostate cancer. As the first diagnostic test, the digital rectal examination is used since malignancy changes the prostate morphology and affects its mechanical properties. Currently, this examination is performed manually by the physician, with an unsatisfactory positive predictive value of 42%. A more objective and spatially selective technique is expected to provide a better prediction degree and understanding of the disease. To this aim, here we propose a miniaturized probe, based on optical fiber sensor technology, for mechanical characterization of the prostate with sub-millimeter resolution. Specifically, the optical system incorporates a customized Fiber Bragg Grating, judiciously integrated in a metallic cannula and moved by a robotic arm. The probe enables the local measurement of the force upon tissue indentation with a resolution of 0.97 mN. The system has been developed in such a way to be potentially used directly in vivo. Measurements performed on phantom tissues mimicking different stages of the prostatic carcinoma demonstrated the capability of our device to distinguish healthy from diseased zones of the prostate. The study on phantoms has been complemented with preliminary ex vivo experiments on real organs obtained from radical surgeries. Our findings lay the foundation for the development of advanced optical probes that, when integrated inside biopsy needle, are able to perform in vivo direct mechanical measurements with high sensitivity and spatial resolution, opening to new scenarios for early diagnosis and enhanced diagnostic accuracy of prostate cancer.

This paper describes the development of a remote handling control of an anthropomorphic robotic hand, the SCHUNK S5FH, using the human hand as master by measuring its motion with OptiTrack Technology. The goal of this work is to enhance manipulation studies on the human hand and to instantly transfer those studies on robotic hands. A preliminary study on methods and devices used for fingers tracking led to the choice of a simplified kinematic model of the human hand on the basis of the available motion tracking system. Using the same criteria, the analysis of protocols for markers allocation led to define the number and a method for their arrangement on the fingers and palm. In order to overcome the limitation of the Motion Capture System, a method for identification and labeling has been developed according to their anatomical arrangement. Afterwards, the tracking is performed using the constraints between marker positions on the kinematic chain of the hand and a dynamic labeling algorithm robust with respect to noise, outliers and loss of markers. The validation is performed using the right hand of different subjects and considering different tasks involving flexion/extension and abduction/adduction of fingers and thumb opposition. For testing and validation, preliminary studies on synergies for manipulation tasks such as screwing a cup, has been conducted on the human hand and transferred on the robotic hand.

This paper presents a new linear velocity estimator based on the unscented Kalman filter and making use of image information aided with inertial measurements. The proposed technique is independent of the scale factor in case of planar observed scene and does not require a priori knowledge of the scene. Image moments of virtual objects, i.e. sets of classical image features such as corners collected online, are employed as the sole correcting information to be fed back to the estimator. Experimental results performed with a quadrotor equipped with a fisheye camera highlight the potential of the proposed approach.

The goal of this paper is to disseminate the main results achieved within the FlexARM project. The project deals with advanced modeling techniques and predictive control strategies for flexible mechanical systems intended to be used in remote tasks inside advanced nuclear fusion reactors. This article aims at underlying the main aspect of the FlexARM methodology and paves the way towards future research in the field. © 2019 EUROfusion Consortium

In this paper, a method to derive the synergies subspace of an anthropomorphic robotic arm–hand system is proposed. Several human demonstrations of different objects grasping are measured using the Xsens MVN suite and then mapped to a seven Degree-of-Freedom (DoF) robotic arm. Exploiting the anthropomorphism of the kinematic structure of the manipulator, two Closed-Loop Inverse Kinematics (CLIK) algorithms are used to reproduce accurately the master’s movements. Once the database of movements is created, the synergies subspace are derived applying the Multivariate Functional Principal Component Analysis (MFPCA) in the joint space. A mean function, a set of basis functions for each joint and a pre-defined number of scalar coefficients are obtained for each demonstration. In the computed subspace each demonstration can be parametrized by means of a few number of coefficients, preserving the major variance of the entire movement. Moreover, a Multilevel Neural Networks (MNNs) is trained in order to approximate the relationship between the object characteristics and the synergies coefficients, allowing generalization for unknown objects. The tests are conducted on a setup composed by a KUKA LWR 4+ Arm and a SCHUNK 5-Finger Hand, using the Xsens MVN suite to acquire the demonstrations.

A method to reconfigure in a nonprehensile way the pose (position and orientation) of a sphere rolling on a plate is proposed in this letter. The nonholonomic nature of the task is first solved at a planning level, where a geometric technique is employed to derive a Cartesian path to steer the sphere towards the arbitrarily desired pose. Then, an integral passivity-based control is designed to track the planned trajectory. The port-Hamiltonian formalism is employed to model the whole dynamics. Two approaches to move the plate are addressed in this paper, showing that only one of them allows the full controllability of the system. A humanoid-like robot is employed to bolster the proposed method experimentally.

This paper presents an experimental study on human-robot comanipulation in the presence of kinematic redundancy. The objective of the work is to enhance the performance during human-robot physical interaction by combining Cartesian impedance modulation and redundancy resolution. Cartesian impedance control is employed to achieve a compliant behavior of the robot's end effector in response to forces exerted by the human operator. Different impedance modulation strategies, which take into account the human's behavior during the interaction, are selected with the support of a simulation study and then experimentally tested on a 7-degree-of-freedom KUKA LWR4. A comparative study to establish the most effective redundancy resolution strategy has been made by evaluating different solutions compatible with the considered task. The experiments have shown that the redundancy, when used to ensure a decoupled apparent inertia at the end effector, allows enlarging the stability region in the impedance parameters space and improving the performance. On the other hand, the variable impedance with a suitable modulation strategy for parameters' tuning outperforms the constant impedance, in the sense that it enhances the comfort perceived by humans during manual guidance and allows reaching a favorable compromise between accuracy and execution time.

In this paper, we propose a nonlinear controller that stabilizes unmanned aerial vehicles in GPS-denied environments with respect to visual targets by using only onboard sensing. The translational velocity of the vehicle is estimated online with a nonlinear observer, which exploits spherical visual features as the main source of information. With the proposed solution, only four visual features have shown to be enough for the observer to operate in a real scenario. In addition, the observer is computationally light with constant numerical complexity, involving small-dimension matrices. The observer output is then exploited in a nonlinear controller designed with an integral backstepping approach, thus yielding a novel robust control system. By means of Lyapunov analysis, the stability of the closed-loop system is proved. Extensive simulation and experimental tests with a quadrotor are carried out to verify the validity and robustness of the proposed approach. The control system runs fully onboard on a standard processor, and only a low-cost sensing suite is employed. Tracking of a target whose speed exceeds 2 $\mathrm{m/s}$ is also considered in the real-hardware experiments.

This paper summarizes recent activities carried out for the development of an innovative anthropomorphic robotic hand called the DEXMART Hand. The main goal of this research is to face the problems that affect current robotic hands by introducing suitable design solutions aimed at achieving simplification and cost reduction while possibly enhancing robustness and performance. While certain aspects of the DEXMART Hand development have been presented in previous papers, this paper is the first to give a comprehensive description of the final hand version and its use to replicate human-like grasping. In this paper, particular emphasis is placed on the kinematics of the fingers and of the thumb, the wrist architecture, the dimensioning of the actuation system, and the final implementation of the position, force and tactile sensors. The paper focuses also on how these solutions have been integrated into the mechanical structure of this innovative robotic hand to enable precise force and displacement control of the whole system. Another important aspect is the lack of suitable control tools that severely limits the development of robotic hand applications. To address this issue, a new method for the observation of human hand behavior during interaction with common day-to-day objects by means of a 3D computer vision system is presented in this work together with a strategy for mapping human hand postures to the robotic hand. A simple control strategy based on postural synergies has been used to reduce the complexity of the grasp planning problem. As a preliminary evaluation of the DEXMART Hand’s capabilities, this approach has been adopted in this paper to simplify and speed up the transfer of human actions to the robotic hand, showing its effectiveness in reproducing human-like grasping.

In this paper, the postural synergy configuration subspace given by the fundamental eigengrasps of the UB Hand IV is derived from experiments, and a simplified synergy-based strategy for planning grasps is proposed. The objectives of this work are, on one side, the simplification of grasp synthesis in a configuration space of reduced dimensions and, on the other side, the attainment of a human-like behavior for anthropomorphic hands. A reference set of 36 hand postures, chosen with the goal of covering the entire grasp variety referring to a recently proposed taxonomy, has been considered for the evaluation of the hand synergies. With the aim of defining general properties of the three predominant synergies, the reference set of hand postures has been applied to other two anthropomorphic robot hands, and the obtained synergies have been compared with the ones computed considering the UB Hand IV kinematics. Moreover, the synthesis of new grasps, not contained in the reference set of hand postures, has also been achieved by means of the synergy subspace. The experiments carried out demonstrate that the adopted synergy-based planning method works efficiently for all the considered grasps even if not contained in the reference set used for the evaluation of the postural synergies. © 2013 Elsevier B.V. All rights reserved.