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

本研究的目的是发展多指机械人手对操作任务状态的精确精细感知能力。以下是研究结果。提出了一种基于位置/力混合控制的基于位置/力混合控制的微型力/扭矩传感器的未知表面形状主动触觉传感方法。针对曲面未知的物体，提出了一种利用表面点的三维数据和主动触觉获取的表面法向信息进行表面重建的方法。提出了一种多指精密滚动接触操作中被操作物体表面指尖滑移检测与测量的新方法。该方法基于视觉多传感器融合、手指关节编码器和指尖力/扭矩传感器。指尖接触的切向滑移位移与指尖滚动运动的位移分离。针对多指操作，提出了几种抓取规划方法。引入了质量措施，以在可能的候选人中选择更好的把握。所述规划器成功地产生了一种能够使被抓物体的运动范围最大化的抓握。建立了钉入孔任务的任务模型。该模型由一系列任务状态转换、运动原语和确定任务状态的过程组成。

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.