Robot instruction by human demonstration

摘要

Conventional methods for programming a robot either are inflexible or demand significant expertise. While the notion of automatic programming by high-level goal specification addresses these issues, the overwhelming complexity of planning manipulator grasps and paths remains a formidable obstacle to practical implementation. This thesis describes the approach of programming a robot by human demonstration. Our system observes a human performing the task, recognizes the human grasp, and maps it onto the manipulator. Using human actions to guide robot execution greatly reduces the planning complexity. In analyzing the task sequence, the system first divides the observed sensory data into meaningful temporal segments, namely the pregrasp, grasp, and manipulation phases. This is achieved by analyzing the human hand motion profiles. The features used are the fingertip polygon area (the fingertip polygon being the polygon whose vertices are the fingertips), hand speed, and the volume sweep r...