The role of morphology of the thumb in anthropomorphic grasping : a review

The unique musculoskeletal structure of the human hand brings in wider dexterous capabilities to grasp and manipulate a repertoire of objects than the non-human primates. It has been widely accepted that the orientation and the position of the thumb plays an important role in this characteristic behavior. There have been numerous attempts to develop anthropomorphic robotic hands with varying levels of success. Nevertheless, manipulation ability in those hands is to be ameliorated even though they can grasp objects successfully. An appropriate model of the thumb is important to manipulate the objects against the fingers and to maintain the stability. Modeling these complex interactions about the mechanical axes of the joints and how to incorporate these joints in robotic thumbs is a challenging task. This article presents a review of the biomechanics of the human thumb and the robotic thumb designs to identify opportunities for future anthropomorphic robotic hands

Human-Robotic Variable-Stiffness Grasps of Small-Fruit Containers Are Successful Even Under Severely Impaired Sensory Feedback

Application areas of robotic grasping extend to delicate objects like groceries. The intrinsic elasticity offered by variable-stiffness actuators (VSA) appears to be promising in terms of being able to adapt to the object shape, to withstand collisions with the environment during the grasp acquisition, and to resist the weight applied to the fingers by a lifted object during the actual grasp. It is hypothesized that these properties are particularly useful in the absence of high-quality sensory feedback, which would otherwise be able to guide the shape adaptation and collision avoidance, and that in this case, VSA hands perform better than hands with fixed stiffness. This hypothesis is tested in an experiment where small-fruit containers are picked and placed using a newly developed variable-stiffness robotic hand. The grasp performance is measured under different sensory feedback conditions: full or impaired visual feedback, full or impaired force feedback. The hand is switched between a variable-stiffness mode and two fixed-stiffness modes. Strategies for modulating the stiffness and exploiting environmental constraints are observed from human operators that control the robotic hand. The results show consistently successful grasps under all stiffness and feedback conditions. However, the performance is affected by the amount of available visual feedback. Different stiffness modes turn out to be beneficial in different feedback conditions and with respect to different performance criteria, but a general advantage of VSA over fixed stiffness cannot be shown for the present task. Guidance of the fingers along cracks and gaps is observed, which may inspire the programming of autonomously grasping robots

Design and development of robust hands for humanoid robots

Design and development of robust hands for humanoid robot

Grasping for the Task:Human Principles for Robot Hands

The significant advances made in the design and construction of anthropomorphic robot hands, endow them with prehensile abilities reaching that of humans. However, using these powerful hands with the same level of expertise that humans display is a big challenge for robots. Traditional approaches use finger-tip (precision) or enveloping (power) methods to generate the best force closure grasps. However, this ignores the variety of prehensile postures available to the hand and also the larger context of arm action. This thesis explores a paradigm for grasp formation based on generating oppositional pressure within the hand, which has been proposed as a functional basis for grasping in humans (MacKenzie and Iberall, 1994). A set of opposition primitives encapsulates the hand's ability to generate oppositional forces. The oppositional intention encoded in a primitive serves as a guide to match the hand to the object, quantify its functional ability and relate this to the arm. In this thesis we leverage the properties of opposition primitives to both interpret grasps formed by humans and to construct grasps for a robot considering the larger context of arm action. In the first part of the thesis we examine the hypothesis that hand representation schemes based on opposition are correlated with hand function. We propose hand-parameters describing oppositional intention and compare these with commonly used methods such as joint angles, joint synergies and shape features. We expect that opposition-based parameterizations, which take an interaction-based perspective of a grasp, are able to discriminate between grasps that are similar in shape but different in functional intent. We test this hypothesis using qualitative assessment of precision and power capabilities found in existing grasp taxonomies. The next part of the thesis presents a general method to recognize oppositional intention manifested in human grasp demonstrations. A data glove instrumented with tactile sensors is used to provide the raw information regarding hand configuration and interaction force. For a grasp combining several cooperating oppositional intentions, hand surfaces can be simultaneously involved in multiple oppositional roles. We characterize the low-level interactions between different surfaces of the hand based on captured interaction force and reconstructed hand surface geometry. This is subsequently used to separate out and prioritize multiple and possibly overlapping oppositional intentions present in the demonstrated grasp. We evaluate our method on several human subjects across a wide range of hand functions. The last part of the thesis applies the properties encoded in opposition primitives to optimize task performance of the arm, for tasks where the arm assumes the dominant role. For these tasks, choosing the strongest power grasp available (from a force-closure sense) may constrain the arm to a sub-optimal configuration. Weaker grasp components impose fewer constraints on the hand, and can therefore explore a wider region of the object relative pose space. We take advantage of this to find the good arm configurations from a task perspective. The final hand-arm configuration is obtained by trading of overall robustness in the grasp with ability of the arm to perform the task. We validate our approach, using the tasks of cutting, hammering, screw-driving and opening a bottle-cap, for both human and robotic hand-arm systems

Simulation-based functional evaluation of anthropomorphic artificial hands.

This thesis proposes an outline for a framework for an evaluation method that takes as an input a model of an artificial hand, which claims to be anthropomorphic, and produces as output the set of tasks that the hand can perform. The framework is based on studying the literature on the anatomy and functionalities of the human hand and methods of implementing these functionalities in artificial systems. The thesis also presents a partial implementation of the framework which focuses on tasks of gesturing and grasping using anthropomorphic postures. This thesis focuses on the evaluation of the intrinsic hardware of robot hands from technical and functional perspectives, including kinematics of the mechanical structure, geometry of the contact surface, and functional force conditions for successful grasps. This thesis does not consider topics related to control or elements of aesthetics of the design of robot hands.The thesis reviews the literature on the anatomy, motion and sensory capabilities, and functionalities of the human hand to define a reference to evaluate artificial hands. It distinguishes between the hand's construction and functionalities and presents a discussion of anthropomorphism that reflects this distinction. It reviews key theory related to artificial hands and notable solutions and existing methods of evaluating artificial hands.The thesis outlines the evaluation framework by defining the action manifold of the anthropomorphic hand, defined as the set of all tasks that a hypothetical ideal anthropomorphic hand should be able to do, and analysing the manifold tasks to determine the hand capabilities involved in the tasks and how to simulate them. A syntax is defined to describe hand tasks and anthropomorphic postures. The action manifold is defined to be used as a. functional reference to evaluate artificial hands' performance.A method to evaluate anthropomorphic postures using Fuzzy logic and a method to evaluate anthropomorphic grasping abilities are proposed and applied on models of the human hand and the InMoov robot hand. The results show the methods' ability to detect successful postures and grasps. Future work towards a full implementation of the framework is suggested

Cognitive Reasoning for Compliant Robot Manipulation

Physically compliant contact is a major element for many tasks in everyday environments. A universal service robot that is utilized to collect leaves in a park, polish a workpiece, or clean solar panels requires the cognition and manipulation capabilities to facilitate such compliant interaction. Evolution equipped humans with advanced mental abilities to envision physical contact situations and their resulting outcome, dexterous motor skills to perform the actions accordingly, as well as a sense of quality to rate the outcome of the task. In order to achieve human-like performance, a robot must provide the necessary methods to represent, plan, execute, and interpret compliant manipulation tasks. This dissertation covers those four steps of reasoning in the concept of intelligent physical compliance. The contributions advance the capabilities of service robots by combining artificial intelligence reasoning methods and control strategies for compliant manipulation. A classification of manipulation tasks is conducted to identify the central research questions of the addressed topic. Novel representations are derived to describe the properties of physical interaction. Special attention is given to wiping tasks which are predominant in everyday environments. It is investigated how symbolic task descriptions can be translated into meaningful robot commands. A particle distribution model is used to plan goal-oriented wiping actions and predict the quality according to the anticipated result. The planned tool motions are converted into the joint space of the humanoid robot Rollin' Justin to perform the tasks in the real world. In order to execute the motions in a physically compliant fashion, a hierarchical whole-body impedance controller is integrated into the framework. The controller is automatically parameterized with respect to the requirements of the particular task. Haptic feedback is utilized to infer contact and interpret the performance semantically. Finally, the robot is able to compensate for possible disturbances as it plans additional recovery motions while effectively closing the cognitive control loop. Among others, the developed concept is applied in an actual space robotics mission, in which an astronaut aboard the International Space Station (ISS) commands Rollin' Justin to maintain a Martian solar panel farm in a mock-up environment. This application demonstrates the far-reaching impact of the proposed approach and the associated opportunities that emerge with the availability of cognition-enabled service robots

Approaching human performance: The functionality driven Awiwi robot hand

Humanoid robotics have achieved a remarkable state in recent years. Nowadays humanoids can walk stairs, serve coffee, throw and catch balls and interact with human beings. However, most of these demonstrations and applications take place in well known environments or even in surroundings that have been adapted to the robots capabilities and needs. However, in order to assist the human in every day tasks, the robot has to operate in (partially) unknown environments in most cases. In these unknown environments and in interaction with moving obstacles as well as human beings, collision avoidance is vague notion. Consequently, this dissertation hypothesizes that the operation of humanoid robots outside of environments dedicated to operate the robots implies that robots have to be able to complete tasks even in case of collision. This especially applies to robot hands, since they are the most exposed and fragile part of a humanoid robot. Humanoid robots have to be anthropomorphic in sense of providing not only human-like appearance but also human characteristics. In particular they have to provide: Robustness against impacts, fast dynamics, human-like grasping and manipulation performance To achieve this robustness and fast dynamics, from the author's point of view, a paradigm change has to be done . Future robots have to be able to store energy as suggested by T. Morita [Morita et al. 1999]. In this thesis the anthropomorphic Awiwi Hand is developed, which provides human-like robustness and dynamics as well as grasping performance. To achieve these characteristics, the human anatomy as well as existing robot hands are analyzed. The goal of this analysis is to derive the functionalities needed to achieve real anthropomorphism rather than to blindly copy the human being. These abstract functionalities are then implemented to a robotic hand. The achieved anthropomorphic characteristics of the Awiwi Hand are demonstrated in several experiments. The Awiwi Hand is able to withstand the impact of a 500 g hammer at high velocity without any damage. It can still keep objects firmly grasped even when struck by an 750 g object at a speed of approximately 4 m/s. The energy stored in the elastic elements of its antagonistic drive train allows the fingers of the hand to achieve a maximum finger speed of approximately 3500 grad/s which is more than five times the speed provided by the drives alone. The Awiwi Hand is, to the author’s knowledge, the first robot hand able to perform all grasps of M. Cutkoskys grasp taxonomy [Cutkosky 1989]. The robustness, fast dynamics and grasping performance of the Awiwi Hand is thought to enable future humanoid robots to operate in "field robotics" rather than in laboratories built for the robots. It will speed up the development of robotic applications since developers will no longer have to bother to avoid possibly costly collisions of the robot. Methods such as reinforcement learning, which need failed task execution attempts to succeed, can be used without fears of severely damaging the robot. The method underlying this development is not limited to robot hands. The proposed methodology will help realize a new generation of humanoid robots that can assist the human being even in harsh environments without damage and for example might fall over without damage. They will hopefully accommodate the demand of the human society for robot assistants that is well documented by the public interest in humanoid robotics

Approaching Human Performance - The Functionality-Driven Awiwi Robot Hand

Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robot for field robotics, where collisions become an unavoidable part of the game. The author argues that the design goal should be real anthropomorphism, as opposed to mere human-like appearance. He deduces three major characteristics to aim for when designing a humanoid robot, particularly robot hands: _ Robustness against impacts _ Fast dynamics _ Human-like grasping and manipulation performance Instead of blindly copying human anatomy, this book opts for a holistic design me-tho-do-lo-gy. It analyzes human hands and existing robot hands to elucidate the important functionalities that are the building blocks toward these necessary characteristics.They are the keys to designing an anthropomorphic robot hand, as illustrated in the high performance anthropomorphic Awiwi Hand presented in this book. This is not only a handbook for robot hand designers. It gives a comprehensive survey and analysis of the state of the art in robot hands as well as the human anatomy. It is also aimed at researchers and roboticists interested in the underlying functionalities of hands, grasping and manipulation. The methodology of functional abstraction is not limited to robot hands, it can also help realize a new generation of humanoid robots to accommodate a broader spectrum of the needs of human society