信頼性の高い身体支援のための関節空間参照多様体の学習
Learning Joint Space Reference Manifold for Reliable Physical Assistance
人型ロボットTalosが着座・起立支援を行う際に、人間の予測不能な力を考慮しつつ安定性を保つため、関節空間における1次元参照多様体を最適化で求める手法を提案した。
著者: Amirreza Razmjoo, Tilen Brecelj, Kristina Savevska, Aleš Ude, Tadej Petrič, Sylvain Calinon
分類: cs.RO
原文アブストラクト
This paper presents a study on the use of the Talos humanoid robot for performing assistive sit-to-stand or stand-to-sit tasks. In such tasks, the human exerts a large amount of force (100--200 N) within a very short time (2--8 s), posing significant challenges in terms of human unpredictability and robot stability control. To address these challenges, we propose an approach for finding a spatial reference for the robot, which allows the robot to move according to the force exerted by the human and control its stability during the task. Specifically, we focus on the problem of finding a 1D manifold for the robot, while assuming a simple controller to guide its movement on this manifold. To achieve this, we use a functional representation to parameterize the manifold and solve an optimization problem that takes into account the robot's stability and the unpredictability of human behavior. We demonstrate the effectiveness of our approach through simulations and experiments with the Talos robot, showing robustness and adaptability.
関連論文
- 身体支援ロボット開発におけるユーザー参加型アプローチの多様な実践身体支援ロボティクス
