任意ボディガード：アクションマスキングによる操作ポリシーの普遍的安全保護
Any-Body Guard: Universal Safeguarding for Manipulation Policies via Action Masking
ロボット操作ポリシーの安全性を、構成空間で直接推論し、衝突回避の形式的確率的保証を提供する普遍的な安全保護手法X-Safeを提案。多様なロボット形態やタスクに追加データやエンジニアリングなしで適用可能。
著者: Alex Beaudin, Hanna Krasowski, Kartik Nagpal, Sanjit A. Seshia, Murat Arcak, Negar Mehr
分類: cs.RO, cs.LG, eess.SY
原文アブストラクト
Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing approaches typically rely on heuristically designed fallback controllers or complex forward invariance assessments. These methods are often too conservative for task success, too computationally expensive for real-time execution, too heuristic to provide useful safety guarantees, or too engineering-heavy to transfer between setups. In this paper, we propose a universal safeguarding approach, X-Safe, which reasons directly in the robot's configuration space to provide formal probabilistic guarantees for collision avoidance. By operating in the configuration space, our method transfers across embodiments while relying solely on an object-based, quasi-static scene representation and a forward kinematics model of the robotic manipulator. Thus, X-Safe provides useful formal safety guarantees without requiring additional data, or engineering effort for different embodiments or scenes. We demonstrate X-Safe for diverse embodiments and policies, both in simulation and on hardware. We observe less degradation in task performance compared to state-of-the-art safeguarding, no collisions on hardware experiments, and empirically corroborate our formal guarantees.