Editorial: A human perspective on robotic hand design, analysis, control and beyond

After introductory considerations on the main functional and design differences between anthropomorphic hands conceived as robotic end effectors or as prostheses, this chapter presents two topics related to advances in robotic hand design that seem transferable to prosthetic hands, in order to increase their functional capability yet coping with specific constraints like simplicity, lightweight, cost effectiveness, robustness, etc. The development of a bio-inspired robotic hand, called UB Hand IV, based on an endoskeletal articulated structure, actuated by tendons and covered by a soft dermal-epidermal layer is briefly illustrated, in order to show the potential of its design solutions to be transferred into prosthetic hands. The first part of the chapter presents alternative design approaches for articulated joints and finger structures based on purposely designed compliant hinges. The basic problem of compliant hinges adoption in robotic structures, that is the limitation of secondary compliance effects, is analyzed and considerations about comparative metrics are proposed. Two hinge morphologies which show promising features are critically compared and pros and cons the production of fully integral fingers with compliant joints are discussed. The second part reports on the development of thin soft covers for robotic (and prosthetic) hands capable of strictly mimicking the actual compliance of human finger pulps. A design method, called by the authors Differentiated Layer Design (DLD), is reviewed and its potential for application on both robotic and prosthetic devices is underlined. Conclusions summarize the main aspects that encourage the transfer of the described results from the world of robots to that of human portable devices.

Recently, research and development has focused on robots that work in place of people. It is necessary for robots to perform the same flexible motions as people. Additionally, such robots need to incorporate high-level safety features in order not to injure people. For creation of such robots, we need to develop a robot hand that functions like a human hand. At the same time, this type of robot hand can be used as an artificial hand. Here, we present artificial muscle-type pneumatic actuators as the driving source of a robot hand that is both safe and flexible. Some development of robot hands using pneumatic actuators has already taken place. However, until now, when a pneumatic actuator is used, a big compressor is needed. Therefore, the driving system also needs to be big, and enlargement of the driving system is a major problem. Consequently, in this research, we develop a low-pressure, low-volume pneumatic actuator for driving a robot hand that works flexibly and safely on the assumption that it will be in contact with people. We develop a five-fingered robot hand with pneumatic actuators. Next, we make a 1-link arm that has one degree of freedom using a pneumatic actuator, and models of the actuator and 1-link arm are constructed. A control PID control system is constructed, and the gains of the PID control system are determined by the simulation that uses the model of the 1-link arm. The step response of the joint angle is examined with the determined gains, and control performance of the PID control system is verified.

Manipulation using dextrous robot hands has been an exciting yet frustrating research topic for the last several years. While significant progress has occurred in the design, construction, and low level control of robotic hands, researchers are up against fundamental problems in developing algorithms for real-time computations in multi-sensory processing and motor control. The aim of this book is to explore parallels in sensorimotor integration in dextrous robot and human hands, addressing the basic question of how the next generation of dextrous hands should evolve. By bringing together experimental psychologists, kinesiologists, computer scientists, electrical engineers, and mechanical engineers, the book covers topics that range from human hand usage in prehension and exploration, to the design and use of robotic sensors and multi-fingered hands, and to control and computational architectures for dextrous hand usage. While the ultimate goal of capturing human hand versatility remains elusive, this book makes an important contribution to the design and control of future dextrous robot hands through a simple underlying message: a topic as complex as dextrous manipulation would best be addressed by collaborative, interdisciplinary research, combining high level and low level views, drawing parallels between human studies and analytic approaches, and integrating sensory data with motor commands. As seen in this text, success has been made through the establishment of such collaborative efforts. The future will hold up to expectations only as researchers become aware of advances in parallel fields and as a common vocabulary emerges from integrated perceptions about manipulation.

Humanoid robots and robotic manipulators with good dexterity are promising to enhance the factory productivity in next generation. Dexterity of robotic manipulators can be achieved by equipping an anthropomorphic robot hand with multiple fingers. Additionally, in order to manipulate various tools that humans are using in daily life, the size and the exerting force of the robot hand should be similar to that humans are. In this paper, we proposed a human-sized multi-fingered robot hand with detachable mechanism at the wrist. The robot hand can be split at the wrist into the hand part and the actuator part. The fingers are driven by wires and are controlled by actuators embedded in the arm part. The driving force from the arm part is transmitted to the hand part by gear mechanism at the wrist. The developed robot hand has the size of 200[mm](length) × 78[mm](width) × 24.6[mm](thickness) and can exert 10[N] at the fingertip. The performance of the developed robot hand was shown by a motion control experiment.

We describe the design of the multi-finger anthropomorphic robotic hand for small-scale industrial applications, called AISRA (Anthropomorphic Interface for Stimulus Robust Applications), which can feel and sense the object that it is holding. The robotic hand was printed using the 3D printer and includes the servo bed for finger movement. The data for object recognition was collected using Leap Motion controller, and Naive Bayes classifier was used for training and classification. We have trained the robotic hand on several monotonous objects used in daily life using supervised machine learning techniques and the gesture data obtained from the Leap Motion controller. The mean accuracy of object recognition achieved is 92.1%. The Naive Bayes algorithm is suitable for using with the robotic hand to predict the shape objects in its hands based on the angular position of its figures. Leap Motion controller provides accurate results and helps to create a dataset of object examples in various forms for the AISRA robotic hand, and can be used to help developing and training 3D-printed anthropomorphic robotic hands. The experiments in object grasping experiments demonstrated that the AISRA robotic hand can grasp objects with different size and shape, and verified the feasibility of robot hand design using low-cost 3D printing technology. The implementation can be used for small-scale industrial applications.

Our paper proposes a tendon-driven robotic finger based on an anatomical model of a human finger and a suitable method for its analysis. Our study aims to realize an anthropomorphic robotic hand that has the same characteristics and dexterity as that of a human hand, and it also aims to identify the advantages of the human musculoskeletal structure for application to the design and control of robot manipulators. When designing an anthropomorphic robotic hand, several devices are required to apply the human finger structure to a tendon-driven robotic finger. Reasons for this include that one of the human finger muscles, namely, the lumbrical muscle, is situated between tendons, which is an unfavorable configuration for the tendon-driven mechanism. Second, unlike a standard pulley used in a tendon-driven mechanism, some moment arms of the human finger change nonlinearly according to the joint angle. In our robotic finger design, we address these difficulties by rearranging its tendons and develop a mechanism to change the moment arm. We also propose a method to analyze and control this robotic fingers coordinating joints using non-stretch branching tendons based on the human extensor mechanism with a virtual tendon Jacobian matrix and the advantage is that this constraint virtually reduces the degrees-of-freedom (DOF) of the mechanism. Further, we build a prototype to confirm its motion using this method. In addition, we show that the state with the reduced DOF can be lost by external forces acting on the mechanism, and this condition can be changed manually by adjusting the tendon forces. This makes it possible to control the virtual DOFs to satisfy the requirements of the task. Finally, we discuss the benefits from anthropomorphic structures including the tendon arrangement, which mimic the human lumbrical muscle, and the above mentioned mechanism with non-linear moment arms from the perspective that there are two states of DOFs. These insights may provide new perspectives in the design of robotic hands.

The paper concerns with the intelligent control of an over-actuated robotic arm. First, it will be presented the original mechanical design of the redundant, cable-driven robot arm with 7 degrees of freedom, whose prototype is being built. Then, it will be synthesized, at the high-control level, an intelligent fuzzy controller that manages activation of the redundant number of robot arm actuators. Structure of the fuzzy controller is given in the paper. Then, the intelligent controller will be applied in the frame of a mathematical model of the considered robotic arm. Performance verification of the synthesized intelligent controller of robotic arm will be accomplished by means of several simulation experiments. Corresponding results are presented and analyzed at the end of the paper. Future directions of research and development in this field will be emphasized as well as the expected results and applications to be planned.

This paper proposes a method to design low-cost robotic hands that require almost toolless assembly, and have special transmissions and joint mechanisms. The transmissions consist of active and passive gear trains manufactured by 3D printers to realize coordinated motions among joints and to transmit the driving force to underactuated joints. The joints are designed with pop-in structures to simplify the assembly of the designed robotic hands and its maintenance. The robotic hands even enabled us to exchange some components without necessitating a shutdown. By using these techniques, we manufactured two robotic hands with different passive gear trains. One of the hands had three fingers with stiff constrained gear trains and soft fingertips, and the other had five fingers with elastic gear trains. Experiments were conducted to validate the performance of the proposed robotic hands and to clarify the roles of the different gear trains.

Human finger joints are conventionally simplified as rigid joints in robotic hand design and biomechanical hand modelling, due to their anatomic and morphologic complexity. However, our understanding of the effect of the finger joint configuration on the resulting hand performance is still primitive. In this study, we systematically investigate the grasping performance of the hands with the conventional rigid joints and the biomechanical flexible joints based on a computational human hand model. The measured muscle electromyography (EMG) and hand kinematic data during grasping are used as inputs for the grasping simulations. The results show that the rigid joint configuration currently used in most robotic hands leads to large reductions in hand contact force, contact pressure and contact area, compared to the flexible joint configuration. The grasping quality could be reduced up to 40% and 36% by the rigid joint configuration in terms of algebraic properties of grasping matrix and finger force limit respectively. Further investigation reveals that these reductions are caused by the weak rotational stiffness of the rigid joint configuration. This study implies that robotic/prosthetic hand performance could be improved by exploiting flexible finger joint design. Hand contact parameters and grasping performance may be underestimated by the rigid joint simplification in human hand modelling.

In this study, a Crossed Flexural Hinge (CFH) structure was used for the design of a humanoid robot hand that can absorb any abrupt external force and that has a large payload, giving it the advantages of both rigid and compliant robots. Structural problems were identified through a 6 × 6 stiffness matrix to analyze whether CFH is suitable for use as an anthropomorphic robot hand. To reinforce the weak stiffness, a paired CFH (p-CFH) structure was proposed for the robot hand joints. In addition, it was verified through theoretical and experimental methods that p-CFH has superior stiffness characteristics compared to conventional CFH. When designing the anthropomorphic robot hand, p-CFH was appropriately deformed and applied. Using an underactuated wire mechanism suitable for the structure of the robot hand, it was possible to grasp objects of various shapes in a shape-adaptive manner. It was confirmed that the final anthropomorphic robot hand was able to stably hold an object of an unspecified shape without precisely controlling the motor. And the robot hand can also hold a heavy object due to the increased rigidity of the p-CFH. In addition, by conducting the qualitative impact test in which the robot was subjected to an impact in an arbitrary direction, it was confirmed that the robot, due to compliance of the joints, can absorb impact without incurring damage. Finally, a quantitative impact test was conducted in all directions, and the shock absorbing capability of anthropomorphic robot hand was verified through numerical comparison with the control model.

A bionic robotic hand can perform many movements similar to a human hand. However, there is still a significant gap in manipulation between robot and human hands. It is necessary to understand the finger kinematics and motion patterns of human hands to improve the performance of robotic hands. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hands of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a larger dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Additionally, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by the PIP joint. Regarding the finger sequence, the thumb started to move before the four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided a kinematic reference for the design of robotic hands and thus contributes to its development.

With demographic change driving the demand for robotic assistance in complex grasping tasks, robot hands are emerging as a promising solution. However, the growing interest in anthropomorphic robot hands is difficult to address: The complex and multifaceted mechanical design creates high entry hurdles for new designers. This slows the growth in the number of experts and complicates finding relevant information, even for experienced designers. This is particularly evident in the conceptual design phase, when determining joint configuration, their coordination, and relative allocation. Guidance in the form of a knowledge-based design assistance system could address these problems by automating the decision-making parts of the design process, presenting solutions with reference to literature and offering recommendations for the conceptual design. This dissertation addresses the question of how such a guidance can be developed. A hypotheses is formulated and three objectives are pursued to test it: (1) develop a literature-linked knowledge base on joint configuration and coordination of tendon-driven rigid-sequential anthropomorphic robot hands to systematically generate conceptual designs, (2) develop a method to identify optimal designs based on user requirements, and (3) develop an automated evaluation method to select the most suitable design from the generated options. For the first objective, a knowledge base is developed, organizing relevant information into a non-redundant list of 23 fields of interest and 30 principal solutions, each linked to its original references. Arranged in morphological boxes, the knowledge base is applied to a methodically derived joint configuration of the human hand to generate approximately 8.5 billion conceptual designs. For the second, a heuristic is developed to identify Pareto-optimal designs based on desired grasp types (performance) and a choice between dexterity and design simplicity (preference). Suitable joint configurations and coordination strategies, drawn from literature, are ranked according to the user’s preference. For the third, the developed control system evaluates designs using a utility analysis of the principal solutions, with scores adjusted by preference and relevance weights to align with the heuristic. The resulting guidance is implemented as a graphical user interface and verified to replicate the intended recommendations. An example application of the guidance presents, to the best of the author’s knowledge, the first task-based design of an anthropomorphic robot hand with references to original sources. By lowering entry barriers in early-stage anthropomorphic robot hand design, this dissertation lays a foundation for accelerating mechanical and control development, with potential to meet growing demand and reduce costs. It also presents the first framework for task-based robot hand design with meaningful results, despite gaps in the state of the art limiting a full analysis.

Abstract: Providing a robotic system with dexterous skills and autonomous capabilities is a key challenge in the field of humanoid robotics, particularly in areas such as industrial manufacturing, prosthetics, and orthopaedic rehabilitation. Providing such a system would be extremely useful in these areas. In order for its functionality to be fully realised, a multifingered robotic hand calls on a significantly higher level of actuation and transmission systems. Under actuation techniques provide the impression of being a workable solution for achieving high degrees of dexterity in robotic hands without the need for more complex mechanical design. One of the most defining characteristics of an under-actuated robotic hand is that the needed number of actuators to control the hand is fewer in number than the degree of freedom that the hand possesses. When compared to a fully actuated version of the same hand, an identical hand with under actuation offers a considerable reduction in the complexity of the control system and a large cost savings. The current study proposes the design and kinematic analysis of an anthropomorphic five-finger robotic hand. Four of the fingers and the thumb are under-actuated, and the hand has twenty-one degrees of freedom and twelve degrees of actuation.

This paper introduces an anthropomorphic robot hand that has variable grasping stiffness to unknown objects without damage. The robot hand has four fingers, 13 DoFs (Degrees of Freedom) with three SEA (Series Elastic Actuator) modules in the index, middle, and ring finger. The performance for broader grasping stiffness using variable impedance control based on the parameter update block and the procedure of grasping capability evaluations of the robot hand are explained. The robot finger modules are constructed with a thumb, index, middle, and ring finger to complete the anthropomorphic type robot hand. The robot finger module has three DoFs and functions as one actuator based on an under-actuated mechanism. Additionally, external force measurement is possible in the fingertip force sensor and SEA (Series Elastic Actuator) module. For the variable impedance control implementation, a parameter update block is added to adjust the desired impedance parameter. To implement the parameter update block, we define and evaluate the correlation equation between the fingertip force, shore hardness, and damping ratio.

This paper describes how a standard HI-tech WINner Corporation articulated six degrees of freedom (DOFs) industrial robot arm and a National Taiwan University five-finger robotic hand was equipped with additional hardware and software to enable the resulting machine to play chess with a human chess player. For automatic interaction with the human player, moves were recorded by a webcam and automatically analyzed. No manual (keyboard) input was necessary. The chess-playing robotic system has been provided. An innovative humanoid robotic hand with 12 DOFs and 19 joints were designed, and distributed tactile sensor arrays with 376 detecting points on its surface were developed. The hand can communicate with the external through controller area networks bus. For performance evaluation of the designed robotic hand, we analyzed the workspace, intersection volume, and manipulability. First, several anatomical analyses were conducted prior to a decision on the kinematic design. Optimization procedures were then developed in this study to improve the parameters of the design and structure of the mechanism. The concepts of a series elastic actuator and an under-actuated mechanism were also employed to give the robotic hand a compliant property and high dexterity; hence, a humanoid robotic hand was devised. Since the robotic hand is as small and dexterous as a human hand, it can be conveniently used for a wide range of applications. Finally, the system has been proved to be executable in a complex environment.