接触インタラクションの解釈によるロボット組立作業の失敗克服
Interpreting Contact Interactions to Overcome Failure in Robot Assembly Tasks
組立失敗時の触覚センサ情報から部品の位置と種類の信念を更新する微分可能フィルタを学習し、不確実性下でも部品嵌合を成功させる階層的手法を提案した。
著者: Peter A. Zachares, Michelle A. Lee, Wenzhao Lian, Jeannette Bohg
分類: cs.RO
原文アブストラクト
A key challenge towards the goal of multi-part assembly tasks is finding robust sensorimotor control methods in the presence of uncertainty. In contrast to previous works that rely on a priori knowledge on whether two parts match, we aim to learn this through physical interaction. We propose a hierarchical approach that enables a robot to autonomously assemble parts while being uncertain about part types and positions. In particular, our probabilistic approach learns a set of differentiable filters that leverage the tactile sensorimotor trace from failed assembly attempts to update its belief about part position and type. This enables a robot to overcome assembly failure. We demonstrate the effectiveness of our approach on a set of object fitting tasks. The experimental results indicate that our proposed approach achieves higher precision in object position and type estimation, and accomplishes object fitting tasks faster than baselines.
