Human-Aware RRT-Connect: Motion Planning for Safe Human-Robot Collaboration

Abstract

This paper proposes a human-aware motion planner building on RRT-Connect, dubbed Human-Aware RRT-Connect. The planner considers a composite cost function that includes four criteria: human separation distance, human-robot center of mass distance, robot inertia and visibility. This choice of criteria ensures the robot maintains a safe distance and low inertia during motion while being as visible as possible to the human. A simulation study is conducted to demonstrate the planner performance. For the simulation study, the proposed offline Human-Aware RRT-Connect planner is compared to other offline planners through a set of scenarios that vary in environment and task complexity. Several human-robot configurations are tested in a shared workspace involving a simulated Franka Emika Panda arm and a human model. The paths generated by the Human-Aware RRT-Connect planner maintain larger separation distances from the human, are of lower inertia, and are more visible.