Robot Hands

The human hand with more than twenty seven Degrees of Freedom (DoFs) has a unique musco-skeletal structure with neuro-sensory attributes under control of CNS, is a quintessence to construct a robotic hand. The fingers are connected to the palm with metacarpophalangeal (MCP) joints. These joints have two DoFs i.e. flexion-extension and abduction-adduction whereas the remaining two joints of the digits have only one DoF. Literature survey divulges that, while constructing a robotic hand, mostly the abduction-adduction at MCP joint is discarded for simplicity. This paper is aimed at development of a mechanism that encompasses both flexion-extension and abduction-adduction for all the three fingers located on the palm opposite to the thumb, whereas the thumb has been separately designed to impart both the radial and palmer movements with respect to the palm as well as flexion and extension, thereby imparting greater compliance to the system, to cope up with wide variety of tasks. Keywor...

Current anthropomorphic robotic hands mainly focus on improving their dexterity by devising new mechanical structures and actuation systems. However, most of them rely on a single structure/system (e.g., bone-only) and ignore the fact that the human hand is composed of multiple functional structures (e.g., skin, bones, muscles, and tendons). This not only increases the difficulty of the design process but also lowers the robustness and flexibility of the fabricated hand. Besides, other factors like customization, the time and cost for production, and the degree of resemblance between human hands and robotic hands, remain omitted. To tackle these problems, this study proposes a 3D printable multi-layer design that models the hand with the layers of skin, tissues, and bones. The proposed design first obtains the 3D surface model of a target hand via 3D scanning, and then generates the 3D bone models from the surface model based on a fast template matching method. To overcome the disad...

Dedicated experiments using the fabricated prototypes were conducted to evaluate the effectiveness of proposed robotic anthropomorphic system via a series of workspace, grasping, and in-hand manipulation tasks. The proposed BCL-13 hand offers a promising design solution to a light weight, dexterous, affordable, and highly anthropomorphic robotic hand design.

AMADEUS is a dexterous subsea robot hand incorporating force and slip contact sensing, using fluid filled tentacles for fingers. Hydraulic pressure variations in each of three flexible tubes (bellows) in each finger create a bending moment, and consequent motion or increase in contact force during grasping. Such fingers have inherent passive compliance, no moving parts, and are naturally depth pressure-compensated, making them ideal for reliable use in the deep ocean. In addition to the mechanical design, development of the hand has also considered closed loop finger position and force control, coordinated finger motion for grasping, force and slip sensor development/signal processing, and reactive world modeling/planning for supervisory 'blind grasping'. Initially, the application focus is for marine science tasks, but broader roles in offshore oil and gas, salvage, and military use are foreseen. Phase I of the project is complete, with the construction of a first prototype. Phase I1 is now underway, to deploy the hand from an underwater robot arm, and carry out wet trials with users.

Several aspects have to be addressed before realizing the dream of a robotic handarm system with human-like capabilities, ranging from the consolidation of a proper mechatronic design, to the development of precise, lightweight sensors and actuators, to the efficient planning and control of the articular forces and motions required for interaction with the environment. This thesis provides solution algorithms for a main problem within the latter aspect, known as the grasp planning problem: Given a robotic system formed by a multifinger hand attached to an arm, and an object to be grasped, both with a known geometry and location in 3-space, determine how the hand-arm system should be moved without colliding with itself or with the environment, in order to firmly grasp the object in a suitable way. Central to our algorithms is the explicit enforcement of a pre-speceified set of handobject contact constraints in the grasp configuration, imposed by the particular manipulation task to be performed with the object. This is a distinguishing feature from other grasp planning algorithms given in the literature, where a means of ensuring precise hand-object contact locations in the resulting grasp is usually not provided. These conventional algorithms are fast, and nicely suited for planning grasps for pickan-place operations with the object, but not for planning grasps required for a specific manipulation of the object, like those necessary for holding a pen, a pair of scissors, or a jeweler's screwdriver, for instance, when writing, cutting a paper, or turning a screw, respectively. To be able to generate such highly-selective grasps, we assume that a number of surface regions on the hand are to be placed in contact with a number of corresponding regions on the object, and enforce the fulfilment of such constraints on the obtained solutions from the very beginning, in addition to the usual constraints of grasp restrainability, manipulability and collision avoidance. The proposed algorithms can be applied to robotic hands of arbitrary structure, possibly considering compliance in the joints and the contacts if desired, and they can accommodate general patch-patch contact constraints, instead of more restrictive contact types occasionally considered in the literature. It is worth noting, also, that while common force-closure or manipulability indices are used to assess the quality I would like to express my gratitude to my advisors Lluís Ros and Raúl Suárez for their invaluable guidance. Also, to Josep M. Porta and Jan Rosell for their unconditional support, and for leading the projects of such wonderful frameworks, the CUIK and Kautham suites, in which this thesis relies on. I would like to thank Federico Thomas who, together with Raúl, came with the idea of joining the worlds of grasping and kinematics that resulted in this PhD research. I am thankful to Antonio Bicchi and Marco Gabiccini for letting me accomplish a fruitful research stay in Pisa; Chapter 5 is a joint work with them. I'd like to highlight the work of Alexander Perez, a friend, a coauthor, and coder of a large part of the Kautham suite; Montserrat Manubens, Léonard Jaillet, Oriol Bohigas, friends and contributors to the CUIK suite; Patrick Grosch, a friend who provided some of the 3D models used here as well as great ideas; and Leopold Palomo, a friend who introduced me to the open source world and provided technical support. Thus, I would like to acknowledge the work of the open source and free software communities since most of the content of this document has been generated using freely-available tools, such as Ubuntu, Debian, LaTeX, Inkscape, GIMP, Geomview, Blender, among many others, freely-available 3D models, such as the SketchUp handarm model used in Figure 1.3 shared by Daniel Murray, and freely-available LaTex templates, such as the PhD thesis style used for this document shared by Adolfo Rodriguez, all of them free as in free beer, and some as in freedom. I would like to acknowledge the reviewing work of numerous researchers who have improved this work with their valuable comments on publications. I'd like to thank my relatives for their support. And last, but not least for sure, I am more than pleased to have met very nice friends and colleagues at the IOC and IRI institutes, as well as countless friends aside who collabarated in different ways and means to the development of this work.

Este trabajo aborda el problema de la sintesis de prensiones con “force-closure” para un objeto articulado 3D constituido por 3 eslabones y considerando contactos sin friccion. La superficie de cada eslabon se representa por medio de un conjunto finito de puntos. En primer lugar se presenta una metodologia por medio de la cual se define el espacio de fuerzas generalizadas generado por fuerzas aplicadas en los eslabones de un objeto articulado 3D. En segundo lugar se describe el algoritmo por medio del cual se calcula el conjunto de puntos que permiten una prension con FC. El enfoque ha sido implementado y en el articulo se incluyen algunos ejemplos ilustrativos.

This paper proposes a method that finds a locally optimal grasp of an articulated 2D object with n links considering frictionless contacts. The surface of each link of the object is represented by a finite set of points, thus it may have any shape. The proposed approach finds, first, an initial force-closure grasp and from it starts an iterative search of a local optimum grasp. The quality measure considered in this work is the largest perturbation wrench that a grasp can resist with independence of the direction of the perturbation. The approach has been implemented and some illustrative examples are included in the article.

AMADEUS is a dexterous subsea robot hand incorporating force and slip contact sensing, using fluid filled tentacles for fingers. Hydraulic pressure variations in each of three flexible tubes (bellows) in each finger create a bending moment, and consequent motion or increase in contact force during grasping. Such fingers have inherent passive compliance, no moving parts, and are naturally depth pressure-compensated, making them ideal for reliable use in the deep ocean. In addition to the mechanical design, development of the hand has also considered closed loop finger position and force control, coordinated finger motion for grasping, force and slip sensor development/signal processing, and reactive world modeling/planning for supervisory 'blind grasping'. Initially, the application focus is for marine science tasks, but broader roles in offshore oil and gas, salvage, and military use are foreseen. Phase I of the project is complete, with the construction of a first prototype. Phase I1 is now underway, to deploy the hand from an underwater robot arm, and carry out wet trials with users.

A demonstration of the application of fuzzy logicbased joint controller (FLJC) to a 6-DOF robotic arm as a colorbased sorter system is presented in this study. The robotic arm with FLJC is integrated with a machine vision system that can discriminate different colors. Additionally, the machine vision system composed of Kinect camera and computer were used to extract the coordinates of the gripper and the objects within the image of the workspace. A graphical user interface with an underlying sorting algorithm allows the user to control the sorting process. Once the system is configured, the computed joint angles by FLJC are transmitted serially to the microcontroller. The results show that the absolute error of the gripper coordinates is less than 2 cm and that the machine vision is capable of achieving at least 95% accuracy in proper color discrimination both for first and second level stacked color objects.

This paper presents a review on main topic regarding to anthropomorphic robotic hands developed in the last years, taking into account the more important mechatronics designs submit on the literature, and making a comparison between them. The next chapters deepen on level of anthropomorphism and dexterity in advanced actuated hands and upper limbs prostheses, as well as a brief overview on issues such as grasping, transmission mechanisms, sensory and actuator system, and also a short introduction on under-actuated robotic hands is reported.

This paper presents a review on main topic regarding to anthropomorphic robotic hands developed in the last years, taking into account the more important mechatronics designs submit on the literature, and making a comparison between them. The next chapters deepen on level of anthropomorphism and dexterity in advanced actuated hands and upper limbs prostheses, as well as a brief overview on issues such as grasping, transmission mechanisms, sensory and actuator system, and also a short introduction on under-actuated robotic hands is reported.

Tactile sensing is an essential element of autonomous dexterous robot hand manipulation. It provides information about forces of interaction and surface properties at points of contact between the robot fingers and the objects. Recent advancements in robot tactile sensing led to development of many computational techniques that exploit this important sensory channel. This paper reviews current state-of-the-art of manipulation and grasping applications that involve artificial sense of touch and discusses pros and cons of each technique. The main issues of artificial tactile sensing are addressed. General requirements of a tactile sensor are briefly discussed and the main transduction technologies are analyzed. Twenty eight various tactile sensors, each integrated into a robot hand, are classified in accordance with their transduction types and applications. Previously issued reviews are focused on hardware part of tactile sensors, whereas we present an overview of algorithms and tactile feedback-based control systems that exploit signals from the sensors. The applications of these algorithms include grasp stability estimation, tactile object recognition, tactile servoing and force control. Drawing from advancements in tactile sensing technology and taking into consideration its drawbacks, this paper outlines possible new directions of research in dexterous manipulation.

In this paper, we propose a robust control framework for object manipulation for when the robotic hand has limited knowledge of the grasp scenario. The framework considers a hand-object system subject to disturbances resulting from uncertainties in the object center of mass/inertia, hand kinematics, external wrenches, and contact locations. The framework guarantees semi-global asymptotic stability and exponential stability of the uncertain hand-object system with respect to object manipulation. The proposed framework is then applied to practical object manipulation scenarios with different levels of uncertainty related to the sensors available to the robotic hand. These scenarios include when the hand-object system is known perfectly; when vision sensors are available; when tactile sensors are available; and when no vision/tactile sensors are available to the robotic hand (i.e. blind grasping). The analysis also addresses the internal force control in relation to the various practic...

Tactile-based blind grasping addresses realistic robotic grasping in which the hand only has access to proprioceptive and tactile sensors. The robotic hand has no prior knowledge of the object/grasp properties, such as object weight, inertia, and shape. There exists no manipulation controller that rigorously guarantees object manipulation in such a setting. Here, a robust control law is proposed for object manipulation in tactile-based blind grasping. The analysis ensures semi-global asymptotic and exponential stability in the presence of model uncertainties and external disturbances that are neglected in related work. Simulation and hardware results validate the effectiveness of the proposed approach.

This paper proposes a soft sensor embedded in a soft ring actuator with five fingers as a soft hand to identify the bifurcation of manipulated objects during the inhand manipulation process. The manipulation is performed by breaking the symmetry method with an underactuated control system by bifurcating the object to clockwise or counterclockwise rotations. Two soft sensors are embedded in parallel over a single soft finger, and the difference in the resistance measurements is compared when the finger is displaced or bent in a particular direction, which can identify the bifurcation direction and aid in the break of symmetry approach without the need of external tracking devices. The sensors performance is also characterised by extending and bending the finger without an object interaction. During an experiment that performs a break of symmetry, manipulated objects turn clockwise and counterclockwise depending on the perturbation and actuation frequency, sensors can track the direction of rotation. The embedded sensors provide a self-sensing capability for implementing a closed-loop control in future work. The soft ring actuator performance presents a self-organisation behaviour with soft fingers rotating an object without a required control for rotating the object. Therefore, the soft fingers are an underactuated system with complex behaviour when interacting with objects that serve in-hand manipulation field.

Additive manufacturing has begun to revolutionize the production of various physical technologies that depend on bespoke geometry and tailored material properties for function. This includes the design of compliant mechanisms, which rely on an integral coupling between geometric and material parameters to attain the elastic flexibility necessary to accommodate programmed deformation. While kinetic structures with compliant parts are typically activated by the application of a mechanical force, alternative means of achieving motion are available, such as the use of smart, 4D, or stimuli-responsive materials which react to environmental conditions. In this research, a combination of compliant mechanisms and water-responsive chitosan biopolymers was explored to create flexible, programmable passive actuators, enabled by 3D printing. A set of compliant joints were modeled, simulated, fabricated, and tested to determine the optimal design for use in the actuator. The actuator was then it...

Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geo metry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies-postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.

In this study, an electromyogram (EMG)based human machine interface system is designed and implemented. System acquires EMG signals and processes them to generate commands to control a robotic arm. Different signal processing methodologies are investigated, realized, and compared. The thesis study includes design and implementation of an 8 channels electromyogram data acquisition system which is used to record raw EMG signals from operator’s muscles. The system transfers raw EMG data to control software via USB. Control software processes the raw EMG data accordingly and generates control commands which are used to control the robotic arm. The robotic arm “AL5D” and its actuator driver which are used in thesis are not designed in the scope of this study. They are commercial products which are purchased from Lynxmotion Company. There are five servo motors placed on the robotic arm to realize movements. Communication with the robotic arm is achieved via USB so that the system may be i...

Additive manufacturing has begun to revolutionize the production of various physical technologies that depend on bespoke geometry and tailored material properties for function. This includes the design of compliant mechanisms, which rely on an integral coupling between geometric and material parameters to attain the elastic flexibility necessary to accommodate programmed deformation. While kinetic structures with compliant parts are typically activated by the application of a mechanical force, alternative means of achieving motion are available, such as the use of smart, 4D, or stimuli-responsive materials which react to environmental conditions. In this research, a combination of compliant mechanisms and water-responsive chitosan biopolymers was explored to create flexible, programmable passive actuators, enabled by 3D printing. A set of compliant joints were modeled, simulated, fabricated, and tested to determine the optimal design for use in the actuator. The actuator was then it...

The field of rehabilitation and assistive devices is being disrupted by innovations in desktop 3D printers and open-source designs. For upper limb prosthetics, those technologies have demonstrated a strong potential to aid those with missing hands. However, there are basic interfacing issues that need to be addressed for long term usage. The functionality, durability, and the price need to be considered especially for those in difficult living conditions. We evaluated the most popular designs of body-powered, 3D printed prosthetic hands. We selected a representative sample and evaluated its suitability for its grasping postures, durability, and cost. The prosthetic hand can perform three grasping postures out of the 33 grasps that a human hand can do. This corresponds to grasping objects similar to a coin, a golf ball, and a credit card. Results showed that the material used in the hand and the cables can withstand a 22 N normal grasping force, which is acceptable based on standards...

Planning efficiently at task and motion levels allows the setting of new challenges for robotic manipulation problems, like for instance constrained table-top problems for bi-manual robots. In this scope, the appropriate combination of task and motion planning levels plays an important role. Accordingly, a heuristic-based task and motion planning approach is proposed, in which the computation of the heuristic addresses a geometrically relaxed problem, i.e., it only reasons upon objects placements, grasp poses, and inverse kinematics solutions. Motion paths are evaluated lazily, i.e., only after an action has been selected by the heuristic. This reduces the number of calls to the motion planner, while backtracking is reduced because the heuristic captures most of the geometric constraints. The approach has been validated in simulation and on a real robot, with different classes of table-top manipulation problems. Empirical comparison with recent approaches solving similar problems is also reported, showing that the proposed approach results in significant improvement both in terms of planing time and success rate.

Teleoperating a robotic hand with the aid of a sensorized glove presents some particular problems. One such problem is due to the kinematic differences between the human hand and the robotic hand, which do not allow a simple direct mapping of the sensor readings from the glove to the robotic hand. This problem is addressed with different types of mapping, but none of them is of general use. This paper proposes two new mappings within two existing mapping types, as well as a new hybrid mapping that combines the best features of these existing mapping types. This hybrid mapping allows intuitive free space movements (where the gesture is more important than the precise positions of the fingers) and grasp movements (where the precise positions of the fingers is more important than the gesture), despite kinematic differences between the human hand and the robotic hand. The approach has been implemented and some illustrative examples are presented in the paper.

The planning of collision-free paths for a hand-arm robotic system is a difficult issue due to the large number of degrees of freedom involved and the cluttered environment usually encountered near grasping configurations. To cope with this problem, this paper presents a novel importance sampling method based on the use of Principal Component Analysis (PCA) to enlarge the probability of finding collision-free samples in these difficult regions of the Configuration Space with low clearance. By using collision-free samples near the goal, PCA is periodically applied in order to obtain a sampling volume near the goal that better covers the free space, improving the efficiency of sampling-based path planning methods. The approach has been tested with success on a hand-arm robotic system composed of a four-finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) and an industrial robot (6 independent degrees of freedom).

Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-read...

Soft robotics and under-actuation were recently demonstrated as good approaches for the implementation of humanoid robotic hands. Nevertheless, it is often difficult to increase the number of degrees of actuation of heavily under-actuated hands without compromising their intrinsic simplicity. In this paper we analyze the Pisa/IIT SoftHand and its underlying logic of adaptive synergies, and propose a method to double its number of degree of actuation, with a very reduced impact on its mechanical complexity. This new design paradigm is based on constructive exploitation of friction phenomena. Based on this method, a novel prototype of under-actuated robot hand with two degrees of actuation is proposed, named Pisa/IIT SoftHand+. A preliminary validation of the prototype follows, based on grasping and manipulation examples of some objects.

Soft robotics and under-actuation were recently demonstrated as good approaches for the implementation of humanoid robotic hands. Nevertheless, it is often difficult to increase the number of degrees of actuation of heavily under-actuated hands without compromising their intrinsic simplicity. In this paper we analyze the Pisa/IIT SoftHand and its underlying logic of adaptive synergies, and propose a method to double its number of degree of actuation, with a very reduced impact on its mechanical complexity. This new design paradigm is based on constructive exploitation of friction phenomena. Based on this method, a novel prototype of under-actuated robot hand with two degrees of actuation is proposed, named Pisa/IIT SoftHand+. A preliminary validation of the prototype follows, based on grasping and manipulation examples of some objects.

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.

In this work, we report on the mechanical design and development, the kinematic analysis, and the simulation of a new dexterous robot finger. The robot finger design is based on that of the human counterpart in size, mechanical structure, and range of motion, and exhibits four distinct joint motions (one abduction/adduction or yaw motion, and three flexion/extension or pitch motions), as does the human finger. Three miniature DC motors with built-in encoders drive the yaw motion of the finger and the two innermost pitch joints. The finger therefore has three independent degrees of freedom. The outermost pitch joint of the finger is mechanically coupled to the middle joint, and the design allows for the variation of the ratio of angular speed between the two coupled joint motions. The motors are installed on the finger itself and on the adjoining section of palm, and the required torques at the joints are obtained through speed reduction transmission systems. An analytical study of the finger, including forward and inverse kinematics and differential kinematics analyses, static force analysis, and computation of joint velocity profiles for straight-line motion of the fingertip, has been carried out. The results of these analyses have been used to develop the control program for the finger, as well as a versatile simulation tool that can be used to optimise future designs of the finger. The simulation program has been validated by comparison to the results of tests carried out on the prototype finger. The ultimate aim of the work is to produce a dexterous robot hand to be used in a flexible manufacturing environment in industry or as a prosthetic device.

Over the last decade underactuated, adaptive robot grippers and hands have received an increased interest from the robotics research community. This class of robotic end-effectors can be used in many different fields and scenarios with a very promising application being the development of prosthetic devices. Their suitability for the development of such devices is attributed to the utilization of underactuation that provides increased functionality and dexterity with reduced weight, cost, and control complexity. The most critical components of underactuated, adaptive hands that allow them to perform a broad set of grasp poses are appropriate differential mechanisms that facilitate the actuation of multiple degrees of freedom using a single motor. In this work, we focus on the design, analysis, and experimental validation of a four output geared differential, a series elastic differential, and a whiffletree differential that can incorporate a series of manual and automated locking me...

In this paper the numerical results for the characterization of a new design of an underactuated mechanism for a robotic hand are presented. The hand is composed by a palm and one finger. The finger is actuated by a four-bar mechanism and the palm is composed by two links which are actuated by a spring. The aim of the proposed mechanism is to improve the grasping performance of the LARM hand and avoid to increasing in the number of actuators. The numerical simulations have been carried out using the SolidWorks environment to evaluate the performance of the mechanism on grasping objects with different shapes, the obtained results show the optimal tracking of trajectories of this proposed solution.

Robotic manipulation and assembly of micro and nanocomponents in confined spaces is still a challenge. Indeed, the current proposed solutions that are highly inspired by classical industrial robotics are not currently able to combine precision, compactness, dexterity, and high blocking forces. In a previous work, we proposed 2-D in-hand robotic dexterous manipulation methods of arbitrary shaped objects that considered adhesion forces that exist at the micro and nanoscales. Direct extension of the proposed method to 3-D would involve an exponential increase in complexity. In this paper, we propose an approach that allows to plan for 3-D dexterous in-hand manipulation with a moderate increase in complexity. The main idea is to decompose any 3-D motion into a 3-D translation and three rotations about specific axes related to the object. The obtained simulation results show that 3-D in-hand dexterous micro-manipulation of arbitrary objects in presence of adhesion forces can be planned i...

This work proposes an algorithm for designing a simple End Effector configuration for a robotic arm which is able to grasp a given set of objects. The algorithm searches for a common 3-finger grasp over a set of objects. The search algorithm maps all possible grasps for each object which satisfy a quality criterion and takes into account an external wrench (force and torque) applied to the object. The mapped grasps are represented by feature vectors in a high-dimensional space. This feature vector describes the shape of the gripper. We then generate a database of all possible grasps for each object represented as points in the feature vector space. Then we use another search algorithm for intersecting all points over the entire sets and finding common points suitable for all objects. Each point (feature vector) is the grasp configuration for a group of objects, which implies for the end-effector design. The final step classifies the grasps found to subsets of the objects, according to the common points found, this with preference to find one grasp to all the objects. The algorithm will be useful for assembly line robots in reducing end-effector design time, end-effector manufacturing time and final product cost.

Este trabajo aborda el problema de la síntesis de prensiones con "force-closure" para un objeto articulado 3D constituido por 3 eslabones y considerando contactos sin fricción. La superficie de cada eslabón se representa por medio de un conjunto finito de puntos. En primer lugar se presenta una metodología por medio de la cual se define el espacio de fuerzas generalizadas generado por fuerzas aplicadas en los eslabones de un objeto articulado 3D. En segundo lugar se describe el algoritmo por medio del cual se calcula el conjunto de puntos que permiten una prensión con FC. El enfoque ha sido implementado y en el artículo se incluyen algunos ejemplos ilustrativos.

This paper proposes a method that finds a locally optimal grasp of an articulated 2D object with n links considering frictionless contacts. The surface of each link of the object is represented by a finite set of points, thus it may have any shape. The proposed approach finds, first, an initial force-closure grasp and from it starts an iterative search of a local optimum grasp. The quality measure considered in this work is the largest perturbation wrench that a grasp can resist with independence of the direction of the perturbation. The approach has been implemented and some illustrative examples are included in the article.

This paper proposes a solution to the problem of grasp analysis and synthesis of 2D articulated objects with n links considering frictionless contacts. The boundary of each link of the object is represented by a finite set of boundary points allowing links of any shape to be considered. Grasp analysis is carried out to verify whether a set of contact points on the object boundary allows a force-closure grasp, while the goal of grasp synthesis is to determine a set of contact points that allows a force-closure grasp. The paper describes the process of finding the elements of the generalized wrench vector generated by a force applied to any link of the articulated object and a procedure to search for a force-closure grasp based on these generalized wrenches. The approach has been implemented and some examples are included in the paper.

Current anthropomorphic robotic hands mainly focus on improving their dexterity by devising new mechanical structures and actuation systems. However, most of them rely on a single structure/system (e.g., bone-only) and ignore the fact that the human hand is composed of multiple functional structures (e.g., skin, bones, muscles, and tendons). This not only increases the difficulty of the design process but also lowers the robustness and flexibility of the fabricated hand. Besides, other factors like customization, the time and cost for production, and the degree of resemblance between human hands and robotic hands, remain omitted. To tackle these problems, this study proposes a 3D printable multi-layer design that models the hand with the layers of skin, tissues, and bones. The proposed design first obtains the 3D surface model of a target hand via 3D scanning, and then generates the 3D bone models from the surface model based on a fast template matching method. To overcome the disad...

In recent years, the research community has shown growing interest in adaptive, tendon-driven devices due to their lightweight, compact, and cost-effective designs. These features are made possible by utilizing underactuation, differential mechanisms, and structural compliance, providing a compact form and making such devices a very reasonable choice for the development of affordable, easy to control and easy to maintain prosthetic hands. Despite their long history and the considerable research efforts that have been put into their development, prosthetic hands are still suffering from being bulky, heavy, hard to control, and expensive. In particular, it remains challenging to control modern prosthetic hands with the residual limb muscles using traditional muscle-machine interfaces such as Electromyography. In this paper, we propose an anthropomorphic, lightweight , and affordable prosthetic hand equipped with a five output, series elastic differential mechanism and an armband utilizing a new muscle machine interfacing method that is called Lightmyography (LMG). LMG signals are used to discriminate between different hand gestures in real-time, as well as to control the contact forces exerted by the hand. The efficiency of the proposed prosthetic hand is experimentally validated through three different sets of experiments: i) force exertion experiments, ii) grasping experiments involving everyday life objects, and iii) real-time control using lightmyography signals.

The need for more practical, robust, and affordable prosthetic hands for amputees has led to significant advancements in their functionality. However, the challenge of designing prostheses that balance dexterity, functionality, and affordability still persists. The lack of prosthetic designs that can efficiently address the needs of amputees for both heavy manual labor and social interactions, while also being lightweight and dexterous, is still evident. This paper presents a design for an anthropomorphic, adaptive, lightweight, bodypowered prosthetic hand built for performing Activities of Daily Living using a selectively lockable differential mechanism. The proposed differential mechanism allows the users to flex and lock the prosthesis' fingers in a wide range of poses and grasps. The performance of the body-powered prosthesis is experimentally validated with three different types of experiments: i) object grasping, ii) total grasping strength, and iii) individual finger force exertion. The resultant prosthetic hand is lightweight and comfortable to wear and is adequately capable of grasping a wide range of objects, including items commonly used in cleaning and cooking applications where waterproofness is essential.

Robots have predominantly been used in automating tasks in structured industrial environments, however, with the advances in technology they are starting to take part in roles in dynamic everyday life scenarios. As a result, the tasks executed by robotic systems will also grow in sophistication. Grasping and dexterous manipulation are critical aspects that allow humans to execute these sophisticated tasks, enabling them to interact with their environment. As such, emulating the human hand can be advantageous for interacting with a world designed for humans. However, directly replicating the anatomical structure of the hand produces designs that are fully actuated, expensive, and which require sophisticated controls and sensing to operate efficiently. In this paper, we present two different versions of the New Dexterity adaptive, humanlike robot hand that is capable of executing robust caging grasps under a wide range of environmental uncertainties (e.g., object pose uncertainties). One of the versions has a classic, fixed thumb base while the second one incorporates an additional degree of freedom at the thumb base, which enables a translational motion for repositioning the thumb and adjusting the aperture. This design choice enhances the inhand manipulation capabilities of the robot hand, improving also the power grasping capabilities for larger objects. The performances of the proposed robot hand designs are experimentally validated and compared through three different tests: i) grasping experiments involving everyday-life objects, ii) force experiments that evaluate their force exertion capabilities, and iii) in-hand manipulation experiments that demonstrate and compare their dexterity.

A popular solution for connecting different components in modern electronics, such as mobile phones, laptops, tablets, etc, is the use of flexible flat cables (FFC). Typically, it takes hours of repetition from a highly trained worker, or a high precision autonomous robot with specialised end effectors to reliably manage the installation of these cables. Human workers are prone to error, and cannot work endlessly without a break, while the robots often come with a significant expense, and require a substantial amount of time to program and reprogram. Additionally, the use of sophisticated sensing elements further increases the complexity of the required control system. As a result, the performance and robustness of such systems is far from sufficient, hindering their mass adoption. The manipulation of FFCs is also quite challenging. In this work, we focus on the robotic manipulation of a plethora of flexible cables, proposing a multi-modal gripper with locally-dexterous tips and active fingernails. The fingers of the gripper are equipped with: i) locally-dexterous fingertips that accommodate manipulation-capable degrees of freedom, ii) a combination of Nitinol-based active fingernails and suction cups that allow picking up and handling of cables that rest on flat surfaces, and iii) compliant finger-pads that conform to the object surface to increase grasping stability. The proposed robotic gripper is equipped with a camera and a perception system that allow for the execution of complex cable manipulation and assembly tasks in dynamic environments.

Over the last decade underactuated, adaptive robot grippers and hands have received an increased interest from the robotics research community. This class of robotic end-effectors can be used in many different fields and scenarios with a very promising application being the development of prosthetic devices. Their suitability for the development of such devices is attributed to the utilization of underactuation that provides increased functionality and dexterity with reduced weight, cost, and control complexity. The most critical components of underactuated, adaptive hands that allow them to perform a broad set of grasp poses are appropriate differential mechanisms that facilitate the actuation of multiple degrees of freedom using a single motor. In this work, we focus on the design, analysis, and experimental validation of a four output geared differential, a series elastic differential, and a whiffletree differential that can incorporate a series of manual and automated locking mechanisms. The locking mechanisms have been developed so as to enhance the control of the differential outputs, allowing for efficient grasp selection with a minimal set of actuators. The differential mechanisms are applied to prosthetic hands, comparing them and describing the benefits and the disadvantages of each.

In this study, the static, kinematic and dynamic behaviors of a semi-active hand prosthesis were analyzed numerically. Finite Elements method was used in static analysis and analytical method was used in kinematic and dynamic analysis. The mathematical model of the hand was created in kinematic and dynamic analysis. Using the mathematical model obtained, torque values of 0, 15, 30, 45, 60, 75, 90 degrees were calculated according to the different position angles of the fingers. Examination was performed for 4 fingers (index finger, middle finger, ring finger, little finger) and 5 kg of force was applied to the fingertips perpendicular to the finger plane. In this examination, the forces are divided into 25% for the index finger, 35% for the middle finger, 25% for the ring finger and 15% for the little finger. The results obtained for forces at different angles under the specified conditions were explained. As a result of all these stages, the prosthetic hand was designed. The design...

The paper presents a tool to graphically display the contact forces applied by the fingers of a robotic hand when doing grasping and in-hand manipulation. The forces are computed in two ways, on one side, directly using the measurements of tactile forces in the fingertips and, on the other, using the torques applied by the motors in the finger joints. The implemented tool also allows to command and move the real robotic hand by specifying the complete hand configuration or any single joint, and see graphically the hand simulation. Real results are shown using the Allegro hand with tactile sensors WTS-FT.

This paper presents a simple strategy to allow the rotation of unknown objects using a robotic hand equipped with tactile sensors. The tactile and kinematic information, obtained while that the object is manipulated, is used to determine the hand configurations that change the object position. The approach was successfully tested using an anthropomorphic robotic hand (Allegro Hand), with the fingertips modified to include tactile sensors (WTS-FT). Using three fingers of the hand, everyday objects were successfully rotated without using their model for the determination of the hand movements. Index Terms-Model-free manipulation, tactile sensing, multifingered hand.

This work proposes an approach to manipulate unknown objects based on tactile information. The manipulation can have three goals: the optimization of the hand configuration, the optimization of the grasp quality and the optimization of the object configuration. Three different motion strategies are introduced in order to move the fingers trying to deal with each of the three goals. The strategies can be applied independently or combined in a sequential way. The feasibility of the motion strategies was proven in real experimentation using the Schunk Dexterous Hand SDH2.

This paper presents an approach for the object shape reconstruction based on the object manipulation using tactile information and force feedback. The tactile information collected during the manipulation process and the kinematic information of the hand are used to identify points on the surface of the object in contact with the hand and thus allowing the object shape reconstruction. Distance invariants are measured on the reconstructed object shape in order to perform the object identification. The proposed approach was implemented using the Shunck Dexterous Hand (SDH2). Different tests were performed in real executions and some examples are presented in the paper.