Real-Time Motion Adaptation using Relative Distance Space Representation

Reacting to environment changes is a big challenge for real world robot applications. This paper presents a novel approach that allows the robot to quickly adapt to changes, particularly in the presence of moving targets and dynamic obstacles. Typically, a configuration space replanning or adaptation is required if the environment is changed. Rather, our method aims to maintain a plan, in a relative distance space rather than configuration space, that can be valid in different environments. In addition, we introduce an incremental planning structure that allows us to handle unexpected obstacles that may appear during execution. The main contribution is that the relative distance space representation encodes pose re-targeting, reaching and avoiding tasks within one unified cost term that can be solved in real-time to achieve a fast implementation for high degree of freedom (DOF) robots. We evaluate our method on a 7 DOF LWR robot arm, and a 14 DOF dual-arm Baxter robot.