장애물이 있는 환경하에서 여유자유도 로보트의 지능제어 방법

Intelligent control of redundant manipulator in an environment with obstacles

A neural optimization network is proposed to control the redundant robot manipulators in an environment with the obstacle. The weightings of the network are adjusted by considering both the joint dexterity and the capability of collision avoidance of joint differential motion. The fuzzy rules are proposed to determine the capability of collision avoidance of each joint. To show the validities of the proposed method, computer simulation results are illustrated for the redundant robot of the planner type with three degrees of freedom.