屋外ロボットのための障害物対応自律巡回・ナビゲーション
Obstacle-Aware Autonomous Coverage and Navigation for Outdoor Robots
屋外での長時間巡回を実現するため、RTK-GNSSとEKFによる高精度位置推定、カバレッジプランナの改良、行動木によるミッション管理を統合したROS 2アーキテクチャを提案し、シミュレーションと実機で93〜96%の巡回率を達成した。
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著者: Leonardo Gargani, Matteo Frosi, Matteo Matteucci
分類: cs.RO
原文アブストラクト
Long-duration outdoor coverage with autonomous platforms remains challenging beyond classical planning: deployments face localization drift in open spaces, obstacles in cluttered sites, controller feasibility in turn-heavy maneuvers, and persistent autonomy with energy management. We propose a unified ROS 2 architecture for outdoor coverage that combines coverage planning, robust localization, and Nav2-based execution. A dual-antenna RTK-GNSS fused in an EKF keeps the robot pose, both position and heading, accurate across long missions; three controller-aware refinements are added to a mature coverage planner; a Behavior-Tree mission manager coordinates multi-goal execution, layered recovery, cost-aware goal management, and autonomous docking for return-to-charge. We validate the stack through simulation and real-world trials across multiple outdoor areas with varying geometries and obstacle densities. Overall, these results show that the proposed stack can reliably complete outdoor coverage missions across varied areas, sweeping 93.1% to 96.1% of the planned coverage area.