CVaRバリア関数によるリスク回避型計画：二足歩行ロボットの運動への応用
Risk-Averse Planning via CVaR Barrier Functions: Application to Bipedal Robot Locomotion
最悪ケースの安全性を評価するCVaR安全の概念とCVaRバリア関数を提案し、既存制御器に最小限の干渉でCVaR安全を保証する制御器を差分凸計画で設計、二足歩行ロボットに適用した。
著者: Mohamadreza Ahmadi, Xiaobin Xiong, Aaron D. Ames
分類: cs.RO, math.OC
原文アブストラクト
Enforcing safety in the presence of stochastic uncertainty is a challenging problem. Traditionally, researchers have proposed safety in the statistical mean as a safety measure in this case. However, ensuring safety in the statistical mean is only reasonable if system's safe behavior in the large number of runs is of interest, which precludes the use of mean safety in practical scenarios. In this paper, we propose a risk sensitive notion of safety called conditional-value-at-risk (CVaR) safety, which is concerned with safe performance in the worst case realizations. We introduce CVaR barrier functions as a tool to enforce CVaR-safety and propose conditions for their Boolean compositions. Given a legacy controller, we show that we can design a minimally interfering CVaR-safe controller via solving difference convex programs. We elucidate the proposed method by applying it to a bipedal robot locomotion case study.
