タスク変動に対応する修正型共有自律制御
Corrective Shared Autonomy for Addressing Task Variability
ロボットの自律タスクモデル上で人間が主要な状態変数を修正する共有自律の枠組みを提案し、航空機製造の3タスクでユーザー負担の低さを実証した。
著者: Michael Hagenow, Emmanuel Senft, Robert Radwin, Michael Gleicher, Bilge Mutlu, Michael Zinn
分類: cs.RO
原文アブストラクト
Many tasks, particularly those involving interaction with the environment, are characterized by high variability, making robotic autonomy difficult. One flexible solution is to introduce the input of a human with superior experience and cognitive abilities as part of a shared autonomy policy. However, current methods for shared autonomy are not designed to address the wide range of necessary corrections (e.g., positions, forces, execution rate, etc.) that the user may need to provide to address task variability. In this paper, we present corrective shared autonomy, where users provide corrections to key robot state variables on top of an otherwise autonomous task model. We provide an instantiation of this shared autonomy paradigm and demonstrate its viability and benefits such as low user effort and physical demand via a system-level user study on three tasks involving variability situated in aircraft manufacturing.
