Development Of Robot Hand Research Articles

The development of robot hand with joint torque sensor based on torque control

This paper suggests a low cost joint torque sensor which can be easily attached to each joint of a robot-hand for compliance control. We designed a new joint torque sensor that measures a torque exerting at any location. The design of sensor body is optimized through the structural body analysis. We implemented compliance control through measuring a torque applied to the robot-hand. We proved that the proposed joint torque sensor gives acceptable performance when we control the robot-hand.

2P1-S-080 空気圧アクチュエータを用いたロボットハンドの開発(アクチュエータの機構と制御5,生活を支援するロボメカ技術のメガインテグレーション)

2P1-S-080 空気圧アクチュエータを用いたロボットハンドの開発(アクチュエータの機構と制御5,生活を支援するロボメカ技術のメガインテグレーション)

1A1-N-085 ニューテーションモータの開発 : 第6報 23関節ロボットハンドへの応用(ロボットハンドの機構と把握戦略1,生活を支援するロボメカ技術のメガインテグレーション)

1A1-N-085 ニューテーションモータの開発 : 第6報 23関節ロボットハンドへの応用(ロボットハンドの機構と把握戦略1,生活を支援するロボメカ技術のメガインテグレーション)

플러그묘 이식을 위한 로봇 핸드 개발

플러그묘 이식을 위한 로봇 핸드 개발

A human-like real-time grasp synthesis method for humanoid robot hands

This paper addresses a real-time grasp synthesis of multi-fingered robot hands to find grasp configurations which satisfy the force closure condition of arbitrary shaped objects. We propose a fast and efficient grasp synthesis algorithm for planar polygonal objects, which yields the contact locations on a given polygonal object to obtain a force closure grasp by a multi-fingered robot hand. For an optimum grasp and real-time computation, we develop the preference and the hibernation process and assign the physical constraints of a humanoid hand to the motion of each finger. The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics of human grasping. The proposed method reduces the computational time significantly at the sacrifice of global optimality, and enables grasp posture to be changeable within 2-finger and 3-finger grasp. The performance of the presented algorithm is evaluated via simulation studies to obtain the force-closure grasps of polygonal objects with fingertip grasps. The architecture suggested is verified through experimental implementation to our developed robot hand system by solving 2- or 3-finger grasp synthesis.

Mechanism Design of Anthropomorphic Robot Hand: Gifu Hand I

This paper presents an anthropomorphic robot hand Gifu Hand I, to be used as a platform of robot hand for the study of dexterous manipulation. To perform grasping and manipulation like a human, the Gifu Hand I includes five fingers whose actuators are servomotors built in the palm and fingers. A thumb has four degreeof-freedom (DOF) and four joints, and fingers have three DOF and four joints. Two axes of joints near the palm cross orthogonally at one point like the human hand. The design concept of the anthropomorphic robot hand is presented and mechanisms and specifications of the developed robot hand are shown.

Development of an Anthropomorphic Multi-Fingered Hand and Experiments on Grasping Unknown Objects by Groping.

This paper addresses the development of at three-fingered anthropomorphic hand and discusses a strategy for grasping unknown objects by groping. In the former part of the paper, the design of the developed robot hand is presented. The robot hand has a thumb, an index finger and a middle finger with a total of nine degrees-of-freedom. The location of thumb is designed considering the opposability seen in a human hand. Eighty-seven touch sensors are distributed over the palm and fingers of this hand. In the latter part of this paper, a strategy for grasping unknown objects by groping, using the devoloped hand, is discussed. Groping is a kind of sensing. When the system does not have any models available for the objects to be grasped, active sensing becomes inevitable. The aim of the groping is to find at grasping configuration for the unknown objects. A ball, a can, a cone, at rectangular cube, and cube are chosen as the unknown objects in the experiments. Experimental results demonstrate the capability of the strategy for grasping unknown objects. This strategy needs neither models of the objects nor any complicated computations, and therefore, is useful especially for tasks in the real world.

Development of Robot Hands

Development of Robot Hands