Safe and Efficient Human–Robot Collaboration Part II: Optimal Generalized Human-in-the-Loop Real-Time Motion Generation

Abstract

The coexistence of humans and robots in fenceless robot cells requires robust safety precautions to prevent humans from being injured. Currently, safety is ensured by limiting the robot velocity, force, and power. This results in large cycle times and, hence, very inefficient industrial applications, where no amortization of the robotic system can be expected. In this letter, a novel method for improving the robot performance is presented that still complies with the international safety standards for collaborative robots. The approach of this letter is based on a projection of a human arm motion into the robot's path to estimate a possible collision with the robot. This idea is addressed in an optimization approach by minimizing the time needed by the robot to reach the goal position under human-in-the-loop constraints. The segmented path is optimized by solving a nonlinear programming problem, and the effect of crucial parameters is analyzed. To guarantee a flexible motion of the resulting optimized path, a generalization method using dynamic movement primitives and the compliance of constraints are proposed. Experiments validate this new method that significantly improves the efficiency of human–robot coexistence.