Reactive and Safety-Aware Path Replanning for Collaborative Applications

This paper addresses motion replanning in human-robot collaborative scenarios, with an emphasis on reactivity and safety-compliant efficiency. While existing human-aware motion planners perform well in structured environments, they often struggle with unpredictable human behavior. This can result in safety measures that hinder the robot's performance and overall throughput. This study combines reactive path replanning and a safety-aware cost function, enabling the robot to adapt its path to the changes in the scene in real-time. This solution reduces the execution time and trajectory slowdowns while ensuring safety. Simulations and real-world experiments show the method's effectiveness compared to standard human-robot cooperation approaches, with efficiency enhancements of up to 60%. Note to Practitioners-The ISO/TS 15066 outlines collaborative operations designed to uphold worker safety in human-robot collaboration. While these safety measures lead to robot deceleration to prevent collisions, they can also cause inefficiencies due to robot inactivity. This work introduces a dynamic real-time adaptation of the robot's path, aiming to minimize the execution time while considering safety interventions. In contrast to methods relying on pre-computed trajectories, this approach modifies the robot's path in real-time based on the continuous monitoring of the human state, thereby decreasing safety interventions and downtime, especially in dynamic environments.