Motion planning based on hierarchical knowledge for six legged locomotion robot

Abstract

There are many researches about the motion planning problem. In this field, the main research is into generating motion for a specific robot and task without previously acquired motions. We research motion planning reusing knowledge. It is our object to realize hierarchical knowledge with reuse. We adopt a tree-based representation for expressing the knowledge of the motion and adopt genetic programming as a learning method. We construct the motion planning system using hierarchical knowledge. We apply the proposed method to a six legged locomotion robot to show its applicability.