Robot Motion Planning with Human-Like Motion Patterns based on Human Arm Movement Primitive Chains

Abstract

A novel motion planning method is proposed to generate human-like motion for anthropomorphic robot arms. Its highlight is to consider the robot arm to be human-like not only in its configuration but also in its motion patterns. To achieve this, the intrinsic mechanisms of human arm motion generation are transferred to robot motion planning. First, human arm motion is modeled using human arm motion primitives. The mechanisms of human arm motion generation are dissected from a large number of motion samples, reflected in the types, sequencing and quantification rules/laws of the primitives. Next, the human arm motion patterns are studied based on primitive chains. Finally, a new motion planning method is built that autonomously performs motion pattern decisions, motion time allocation, and joint trajectory generation. The proposed method is validated by a motion planning app and a robot simulation.