Precise and fine sensing of manipulation task state by a robotic hand with Multi-jointed fingers

多关节手指机械手精准感知操作任务状态

基本信息

批准号：
12650429
负责人：
HASEGAWA Tsutomu
金额：
$ 1.98万
依托单位：
Kyushu University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2000
资助国家：
日本
起止时间：
2000 至 2001
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-12650429/
关键词：
robotic hand multi-jointed finger slip detection sensor fusion grasp planning

项目摘要

Objective of this research is to develop a precise and fine sensing ability of manipulation task state by a multi-fingered robotic hand. Followings are the results of the research.A method has been developed for active tactile sensing of shape of unknown surfaces using a miniature force/torque sensor mounted on by sliding motion of the fingertip based on position/force hybrid control. A method of surface reconstruction has been developed for an object with unknown curved surface using 3-D data of points on the surface and the surface normal information obtained by active tactile sensing.A new method has been developed for detection and measurement of fingertip slip on a surface of a manipulated object in a multi-fingered precision manipulation with rolling contact. The method is based on the multi-sensor fusion of vision, joint-encoders of the fingers, and fingertip force/torque sensors. Tangential slip displacement of the fingertip contact is separated from the displacement by rolling motion of the fingertip.Several planning methods of grasp for multi-fingered manipulation have been developed. Quality measures are introduced to select better grasp among possible candidates. The planner succeeded to generate a grasp which enables maximizing the range of motion of the grasped object.Task model for the Peg-in-Hole task has been developed. The model is composed of a sequence of task state transition, motion primitives, and procedures for determining task state.

这项研究的目的是通过多指的机器人手来发展操纵任务状态的精确感应能力。以下是研究的结果。已经开发了一种方法，用于使用基于位置/力混合控制的指尖的滑动运动安装的微型力/扭矩传感器使用微型力量/扭矩传感器进行主动触觉传感。已经为具有未知弯曲表面的物体开发了一种表面重建方法通过滚动接触的多指精密操作中的操纵物体的表面。该方法基于视觉的多传感器融合，手指的联合编码器以及指尖力/扭矩传感器。指尖触点的切向滑移位移通过指尖的滚动运动与位移分离。引入质量措施以选择可能的候选人之间的更好掌握。计划者成功地生成了一个掌握，从而最大程度地提高了握把对象的运动范围。该模型由一系列任务状态过渡，运动原语和确定任务状态的程序组成。