Safe Human–Robot Collaboration With Risk Tunable Control Barrier Functions

Vipul K. Sharma, Pokuang Zhou, Zhengtong Xu, Yu She, S. Sivaranjani

Abstract: In this article, we consider the problem of guaranteeing safety constraint satisfaction in human–robot collaboration (HRC) with uncertain human position. We pose this problem as a chance-constrained problem with safety (chance) constraints represented by uncertain control barrier functions, where the probability of safety constraint satisfaction under uncertainty is bounded by a tunable user-defined risk. We solve this stochastic optimization problem using a sampling-based approach and obtain a risk-tunable controller to safely accomplish HRC tasks. We demonstrate the safety and performance of this approach through both simulation and hardware experiments on a 7 degree-of-freedom Franka–Panda manipulator and characterize the tradeoff between the user-defined risk tolerance and task time efficiency in safety-critical applications.

External IDs:doi:10.1109/tmech.2025.3572047