ケージング方式パーツフィーダのためのパーティクルフィルタを用いた外界センサレス物体判別

抄録

In this work, we developed a sensorless method for discriminating objects caged by a robot hand in a two-dimensional plane, for part feeders based on sensorless in-hand caging manipulation. A particle filter is used to represent possible object shapes in terms of a probability distribution based on only the joint angle information of the hand and refine the dimensions and shapes of the object. We have confirmed the ability of the method to discriminate among several object candidates on a simulation basis, especially based on joint information when objects are jammed.