Dexterous Safe Control for Humanoids in Cluttered Environments via Projected Safe Set Algorithm

TL;DR

This paper introduces the Projected Safe Set Algorithm (p-SSA), a novel control method that ensures safe, feasible humanoid robot operation in cluttered environments by relaxing conflicting safety constraints.

Contribution

The paper presents p-SSA, an extension of safe control algorithms that handles multiple constraints by relaxing conflicts, enabling safe humanoid robot operation in complex settings.

Findings

p-SSA successfully prevents infeasible constraints in complex collision avoidance tasks.

The approach demonstrates robustness and minimal safety violations in simulation and real-world tests.

p-SSA generalizes across tasks with zero parameter tuning.

Abstract

It is critical to ensure safety for humanoid robots in real-world applications without compromising performance. In this paper, we consider the problem of dexterous safety, featuring limb-level geometry constraints for avoiding both external and self-collisions in cluttered environments. Compared to safety with simplified bounding geometries in sprase environments, dexterous safety produces numerous constraints which often lead to infeasible constraint sets when solving for safe robot control. To address this issue, we propose Projected Safe Set Algorithm (p-SSA), an extension of classical safe control algorithms to multi-constraint cases. p-SSA relaxes conflicting constraints in a principled manner, minimizing safety violations to guarantee feasible robot control. We verify our approach in simulation and on a real Unitree G1 humanoid robot performing complex collision avoidance tasks. Results show that p-SSA enables the humanoid to operate robustly in challenging situations with minimal safety violations and directly generalizes to various tasks with zero parameter tuning.