日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2109.13649

Affordance Template Registration via Human-in-the-loop Corrections

Affordance Template Registration via Human-in-the-loop Corrections

シェア:XThreadsFacebookLINEはてブBluesky

著者: Michael Hagenow, Michael Zinn, Terrence Fong, Evan Laske, Kimberly Hambuchen

分類: cs.RO

原文アブストラクト

Affordance Templates (ATs) are a method for parameterizing objects for autonomous robot manipulations. In this approach, instances of an object are registered by positioning a model in a 3D environment, which requires a large amount of user input. We instead propose a registration method which combines autonomy and user corrections. For selected objects, the system determines both the model and corresponding pose autonomously. The user makes corrections only if the model or pose is incorrect. This method increases the level of autonomy compared to existing approaches which can reduce user input and time on task. In this paper, we present an overview of existing methods, a description of our method, preliminary results, and planned future work.