拡張現実を用いた人間の実演によるロボット学習システム
Extended Reality System for Robotic Learning from Human Demonstration
物理ロボットを使わずに拡張現実空間で人間の実演を収集し、ロボットに学習させるRADERシステムを提案し、実機での実演と同等の性能を確認した。
著者: Isaac Ngui, Courtney McBeth, Grace He, André Corrêa Santos, Luciano Soares, Marco Morales, Nancy M. Amato
分類: cs.RO, cs.HC
原文アブストラクト
Many real-world tasks are intuitive for a human to perform, but difficult to encode algorithmically when utilizing a robot to perform the tasks. In these scenarios, robotic systems can benefit from expert demonstrations to learn how to perform each task. In many settings, it may be difficult or unsafe to use a physical robot to provide these demonstrations, for example, considering cooking tasks such as slicing with a knife. Extended reality provides a natural setting for demonstrating robotic trajectories while bypassing safety concerns and providing a broader range of interaction modalities. We propose the Robot Action Demonstration in Extended Reality (RADER) system, a generic extended reality interface for learning from demonstration. We additionally present its application to an existing state-of-the-art learning from demonstration approach and show comparable results between demonstrations given on a physical robot and those given using our extended reality system.
