シナリオサンプリングによる脚式ロボットの安全性テスト・検証・特性評価
On Safety Testing, Validation, and Characterization with Scenario-Sampling: A Case Study of Legged Robots
脚式ロボットの安全性を、潜在的に安全な状態集合の特定とその集合内での安全度の定量化により評価するシナリオサンプリング型テスト枠組みを提案し、複数の最先端歩行制御器に適用して有効性を示した。
著者: Bowen Weng, Guillermo A. Castillo, Wei Zhang, Ayonga Hereid
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
The dynamic response of the legged robot locomotion is non-Lipschitz and can be stochastic due to environmental uncertainties. To test, validate, and characterize the safety performance of legged robots, existing solutions on observed and inferred risk can be incomplete and sampling inefficient. Some formal verification methods suffer from the model precision and other surrogate assumptions. In this paper, we propose a scenario sampling based testing framework that characterizes the overall safety performance of a legged robot by specifying (i) where (in terms of a set of states) the robot is potentially safe, and (ii) how safe the robot is within the specified set. The framework can also help certify the commercial deployment of the legged robot in real-world environment along with human and compare safety performance among legged robots with different mechanical structures and dynamic properties. The proposed framework is further deployed to evaluate a group of state-of-the-art legged robot locomotion controllers from various model-based, deep neural network involved, and reinforcement learning based methods in the literature. Among a series of intended work domains of the studied legged robots (e.g. tracking speed on sloped surface, with abrupt changes on demanded velocity, and against adversarial push-over disturbances), we show that the method can adequately capture the overall safety characterization and the subtle performance insights. Many of the observed safety outcomes, to the best of our knowledge, have never been reported by the existing work in the legged robot literature.
