遠隔ロボット訓練のためのヒューマンマシンインターフェース
Human-Machine Interface for Remote Training of Robot Tasks
視覚による3D手検出とジェスチャ認識、デジタルツインの視覚フィードバック、動的モーションプリミティブを用いて、遠隔地から直感的かつ正確にロボットのタスクを訓練・プログラミングするシステムを提案した。
著者: Jordi Spranger, Roxana Buzatoiu, Athanasios Polydoros, Lazaros Nalpantidis, Evangelos Boukas
分類: cs.RO, cs.CV, cs.LG
原文アブストラクト
Regardless of their industrial or research application, the streamlining of robot operations is limited by the proximity of experienced users to the actual hardware. Be it massive open online robotics courses, crowd-sourcing of robot task training, or remote research on massive robot farms for machine learning, the need to create an apt remote Human-Machine Interface is quite prevalent. The paper at hand proposes a novel solution to the programming/training of remote robots employing an intuitive and accurate user-interface which offers all the benefits of working with real robots without imposing delays and inefficiency. The system includes: a vision-based 3D hand detection and gesture recognition subsystem, a simulated digital twin of a robot as visual feedback, and the "remote" robot learning/executing trajectories using dynamic motion primitives. Our results indicate that the system is a promising solution to the problem of remote training of robot tasks.
