Think Fast, Plan Smart, Stay Safe: Safety-Informed MPPI Compliant With ISO/TS 15066

Direct collaboration between robots and humans requires control strategies that ensure safety without sacrificing efficiency. However, compliance with standards, such as ISO/TS 15066, often leads to overly conservative robot behaviors. This article proposes a safety-informed model predictive path integral (SI-MPPI) control framework that guarantees safety while preserving task performance. The architecture integrates a constrained MPPI planner and a trajectory scaling module. The first explicitly incorporates the safety constraints and adaptively computes the stochastically optimal sequence of safe waypoints in real time. Exploiting the receding horizon principle, it selects control actions that maximize long-term efficiency, deciding whether to reduce speed or deviate from the preplanned path. The second refines these waypoints via spline interpolation and velocity adjustment. The approach has been validated in both simulation and real collaborative tasks with a UR10e manipulator, showing fast adaptation to human motion and improved efficiency compared to a state-of-the-art method, while maintaining full compliance with safety requirements.