CALM: ロボット接近時の構成を考慮した人間介入境界
CALM: Configuration-Aware Human Intervention Boundaries During Robot Approach
ロボットの腕の姿勢が人間の介入距離に与える影響を実験で調べ、構成に応じた介入境界を推定するモデルを提案した。
著者: Xinting Gao, Sipu Zhu, Weimin Zhuang
分類: cs.RO, cs.HC
原文アブストラクト
How robot body configuration shapes human intervention during approach remains underexplored. We conducted a within-participants study with 41 participants, measuring final stopping distance, subjective comfort, and exploratory eye-tracking responses across four humanoid arm configurations and two spatial scales. Full forward arm extension increased stopping distance by approximately 31-36 cm relative to arms-down. Spatial scale primarily affected comfort and pupil responses without a detectable stopping-distance shift. We introduce the Configuration-Aware Limit Model (CALM), which translates stopping-distance distributions into configuration-dependent population-coverage boundaries. Estimated boundaries at 80% coverage ranged from 0.88 to 1.47 m. In an illustrative one-dimensional planning analysis, reconfiguration enabled a 1.10 m approach goal that was unreachable with arms remaining fully extended under the same nominal pointwise 20% intervention-probability constraint. These findings support treating body configuration as a planning variable while distinguishing physical safety, behavioral intervention, and subjective cost.