移動ロボットの人間-AI協調制御における階層的可変自律性ミックスイニシアティブフレームワーク
A Hierarchical Variable Autonomy Mixed-Initiative Framework for Human-Robot Teaming in Mobile Robotics
遠隔操作者とAIエージェントが移動ロボットを協調制御する際の制御権限移譲問題に対し、人間の状態と意図を活用した階層的ミックスイニシアティブ制御切替手法を提案し、シミュレーション実験で衝突減少や切替効率向上を示した。
著者: Dimitris Panagopoulos, Giannis Petousakis, Aniketh Ramesh, Tianshu Ruan, Grigoris Nikolaou, Rustam Stolkin, Manolis Chiou
分類: cs.RO, cs.AI, cs.HC, cs.MA
原文アブストラクト
This paper presents a Mixed-Initiative (MI) framework for addressing the problem of control authority transfer between a remote human operator and an AI agent when cooperatively controlling a mobile robot. Our Hierarchical Expert-guided Mixed-Initiative Control Switcher (HierEMICS) leverages information on the human operator's state and intent. The control switching policies are based on a criticality hierarchy. An experimental evaluation was conducted in a high-fidelity simulated disaster response and remote inspection scenario, comparing HierEMICS with a state-of-the-art Expert-guided Mixed-Initiative Control Switcher (EMICS) in the context of mobile robot navigation. Results suggest that HierEMICS reduces conflicts for control between the human and the AI agent, which is a fundamental challenge in both the MI control paradigm and also in the related shared control paradigm. Additionally, we provide statistically significant evidence of improved, navigational safety (i.e., fewer collisions), LOA switching efficiency, and conflict for control reduction.
関連論文
- 操作者の選好とロボットの制約を考慮した円滑な追従動作のための共有制御遠隔操作・共有制御
