MATE-BT：異種マルチロボットチームの階層分散型ミッション自律性を実現するビヘイビアツリー基盤フレームワーク
MATE-BT: A Behavior-Tree-Based Framework for Hierarchically Decentralized Mission Autonomy in Heterogeneous Multi-Robot Teams
ミッション実行・割当・タスク実行を階層的に分離し、リーダー機の故障時にも権限移譲でミッションを継続できる分散型マルチロボット枠組みを提案し、実機とシミュレーションで有効性を示した。
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著者: Sunbeen Lee, Hoseon Gi, Jik Hur, Inmo Jang
分類: cs.RO
原文アブストラクト
Multi-robot teams executing predefined missions must adapt to runtime changes and sustain mission management despite robot failures. This paper proposes MATE-BT (Mission, Allocation, and Task Execution with Behavior Trees), a hierarchically decentralized framework that separates mission execution, allocation, and task execution. An active onboard leader manages mission progression and team-level task assignment, with authority transferable to another leader-capable robot after failure. Interchangeable decentralized methods resolve target assignments, while each robot adapts its local behavior through planning and acting with behavior trees. Webots simulations and real-robot experiments demonstrate mission continuity despite new targets and robot failures, including active-leader failure. In the physical experiments, all MATE-BT computation runs onboard. Hardware-in-the-loop resource measurements further support onboard execution on Jetson Orin Nano and Raspberry Pi 5. By updating only the affected layers without full-plan regeneration, MATE-BT maintained a response time of approximately 130 ms with 30 robots and 120 targets. Comparisons of four target-assignment plugins reveal scenario-dependent trade-offs between mission completion time and total travel distance.