Design method for an anthropomorphic hand able to gesture and grasp

This paper presents a numerical method to conceive and design the kinematic model of an anthropomorphic robotic hand used for gesturing and grasping. In literature, there are few numerical methods for the finger placement of human-inspired robotic hands. In particular, there are no numerical methods, for the thumb placement, that aim to improve the hand dexterity and grasping capabilities by keeping the hand design close to the human one. While existing models are usually the result of successive parameter adjustments, the proposed method determines the fingers placements by mean of empirical tests. Moreover, a surgery test and the workspace analysis of the whole hand are used to find the best thumb position and orientation according to the hand kinematics and structure. The result is validated through simulation where it is checked that the hand looks well balanced and that it meets our constraints and needs. The presented method provides a numerical tool which allows the easy computation of finger and thumb geometries and base placements for a human-like dexterous robotic hand.Comment: IEEE International Conference on Robotics and Automation, May 2015, Seattle, United States. IEEE, 2015, Proceeding IEEE International Conference on Robotics and Automatio

A novel type of compliant and underactuated robotic hand for dexterous grasping

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The usefulness and versatility of a robotic end-effector depends on the diversity of grasps it can accomplish and also on the complexity of the control methods required to achieve them. We believe that soft hands are able to provide diverse and robust grasping with low control complexity. They possess many mechanical degrees of freedom and are able to implement complex deformations. At the same time, due to the inherent compliance of soft materials, only very few of these mechanical degrees have to be controlled explicitly. Soft hands therefore may combine the best of both worlds. In this paper, we present RBO Hand 2, a highly compliant, underactuated, robust, and dexterous anthropomorphic hand. The hand is inexpensive to manufacture and the morphology can easily be adapted to specific applications. To enable efficient hand design, we derive and evaluate computational models for the mechanical properties of the hand's basic building blocks, called PneuFlex actuators. The versatility of RBO Hand 2 is evaluated by implementing the comprehensive Feix taxonomy of human grasps. The manipulator's capabilities and limits are demonstrated using the Kapandji test and grasping experiments with a variety of objects of varying weight. Furthermore, we demonstrate that the effective dimensionality of grasp postures exceeds the dimensionality of the actuation signals, illustrating that complex grasping behavior can be achieved with relatively simple control

Tele-operated high speed anthropomorphic dextrous hands with object shape and texture identification

This paper reports on the development of two number of robotic hands have been developed which focus on tele-operated high speed anthropomorphic dextrous robotic hands. The aim of developing these hands was to achieve a system that seamlessly interfaced between humans and robots. To provide sensory feedback, to a remote operator tactile sensors were developed to be mounted on the robotic hands. Two systems were developed, the first, being a skin sensor capable of shape reconstruction placed on the palm of the hand to feed back the shape of objects grasped and the second is a highly sensitive tactile array for surface texture identification

Design and development of robust hands for humanoid robots

Design and development of robust hands for humanoid robot

Safe Grasping with a Force Controlled Soft Robotic Hand

Safe yet stable grasping requires a robotic hand to apply sufficient force on the object to immobilize it while keeping it from getting damaged. Soft robotic hands have been proposed for safe grasping due to their passive compliance, but even such a hand can crush objects if the applied force is too high. Thus for safe grasping, regulating the grasping force is of uttermost importance even with soft hands. In this work, we present a force controlled soft hand and use it to achieve safe grasping. To this end, resistive force and bend sensors are integrated in a soft hand, and a data-driven calibration method is proposed to estimate contact interaction forces. Given the force readings, the pneumatic pressures are regulated using a proportional-integral controller to achieve desired force. The controller is experimentally evaluated and benchmarked by grasping easily deformable objects such as plastic and paper cups without neither dropping nor deforming them. Together, the results demonstrate that our force controlled soft hand can grasp deformable objects in a safe yet stable manner.Comment: Accepted to 2020 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2020

Robot's hand and expansions in non-integer bases

We study a robot hand model in the framework of the theory of expansions in non-integer bases. We investigate the reachable workspace and we study some configurations enjoying form closure properties.Comment: 22 pages, 10 figure

Feature Selection for Human Grasping Activity Using Pearson's Correlation Techniques

The algorithm of feature selection is the collective of search technique to categorize features into their evaluation score. There are many methods to determine the feature extraction in human grasping analysis such as statistical features, PCA-best matching unit (PCA-BMU) and sum of movement (SuM). Feature selection is important in order to increase the classification accuracy by removing redundant features. In analyzing the human grasping data, only the best features are selected in order to make classifying more accurate, less redundant and quickly identifiable, especially for the objects grouping. Pearson's correlation or simply known as the angular separation is capable to measure the similarity of two vectors rather than the distance or the dissimilarity between them. Advantages of the Pearson's correlation are that it is easy to work out and it's easy to be interpreted

Evaluation of Foot Kinematic Structure by the Order of Bones' and Joints' Edges

A number of distinct digital images can be formed if human foot is viewed as kinematic structure and later being converted into graphs. The synthetic images portray foot in shapes that are different from actual photographs or radiographs. The images exhibit the adjacency of bones, the incidence among bones and joints, and their paths. This study is done to find ways to represent foot in a different fashion and therefore computationally viable. The foot skeleton is studied and its structural kinematic representation is developed. This representation is later transformed into a graph. The kinematic structure is used to study the foot’s structure for engineering design viewpoints, whereas the graph is used to develop synthetic images so that foot conditions could be evaluated through pixels. This paper discusses and interprets foot conditions and anomalies. The method proposed is a one-dimensional mathematical model that is applicable in evaluating foot conditions

Tactile Gloves for Autonomous Grasping With the NASA/DARPA Robonaut

Tactile data from rugged gloves are providing the foundation for developing autonomous grasping skills for the NASA/DARPA Robonaut, a dexterous humanoid robot. These custom gloves compliment the human like dexterity available in the Robonaut hands. Multiple versions of the gloves are discussed, showing a progression in using advanced materials and construction techniques to enhance sensitivity and overall sensor coverage. The force data provided by the gloves can be used to improve dexterous, tool and power grasping primitives. Experiments with the latest gloves focus on the use of tools, specifically a power drill used to approximate an astronaut's torque tool