Vision-based motion recognition of the hexapod for autonomous assistance

Abstract

In a cooperatzon style in which a human operates one robot and thc other autonomous robots assist that robot, the autonomous robots must be able to recognize the motion of tht: human operating robot in real time. Vision is the most useful sensor for this purpose. By using vision, the assistant robot recognizes the current target object and actions of the human operating robot to the target. For the working robots, we use t,wo hexapod robots which #are able to utilize two forelegs as arms in order to manipulate objects. Joint motion of each leg and occlusion by another leg make it di 'cul t to recognize and track the motion of the hexapod robot. In this study, we prcNpose a method for the recognition and tracking of the 3D position and posture of the hexapod. Through the use o f 2 0 image matching, the body of the hexapod, several legs, and toes of the legs can be recognized in turn. T,he positions of the body and toes are measured by binoldar-stereo, and the angles of the legs can then be obtai,ned, which are used for motion recognition. In this study, we propose a motion recognition mechanism using eigenspace method which can reduce the dimensions necessary for matching. The effectiveness of this method is tested through an experiment using two hexapod robots.