「取ってそこに置いて」:人とロボットの協働における明示的・暗黙的タスク割当手法の検討
"Grip-that-there": An Investigation of Explicit and Implicit Task Allocation Techniques for Human-Robot Collaboration
VR上の卓上協働シミュレーションで、ユーザーが主導権を持つ明示的タスク割当と自動化を活かす暗黙的タスク割当を比較し、暗黙的手法が効率的な並列作業を可能にしつつ明示的制御の併用が有効だと示した研究。
著者: Karthik Mahadevan, Maurício Sousa, Anthony Tang, Tovi Grossman
分類: cs.RO, cs.HC
原文アブストラクト
In ad-hoc human-robot collaboration (HRC), humans and robots work on a task without pre-planning the robot's actions prior to execution; instead, task allocation occurs in real-time. However, prior research has largely focused on task allocations that are pre-planned - there has not been a comprehensive exploration or evaluation of techniques where task allocation is adjusted in real-time. Inspired by HCI research on territoriality and proxemics, we propose a design space of novel task allocation techniques including both explicit techniques, where the user maintains agency, and implicit techniques, where the efficiency of automation can be leveraged. The techniques were implemented and evaluated using a tabletop HRC simulation in VR. A 16-participant study, which presented variations of a collaborative block stacking task, showed that implicit techniques enable efficient task completion and task parallelization, and should be augmented with explicit mechanisms to provide users with fine-grained control.
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