不確実環境における巡回監視のための適応的検査計画手法
An Adaptive Inspection Planning Approach Towards Routine Monitoring in Uncertain Environments
環境の変化や障害物に対応するため、検査タスクを大域的な視点計画と局所的な再計画に階層化し、四足歩行ロボットによる実世界の鉱山での検証を行った。
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著者: Vignesh Kottayam Viswanathan, Yifan Bai, Scott Fredriksson, Sumeet Satpute, Christoforos Kanellakis, George Nikolakopoulos
分類: cs.RO
原文アブストラクト
In this work, we present a hierarchical framework designed to support robotic inspection under environment uncertainty. By leveraging a known environment model, existing methods plan and safely track inspection routes to visit points of interest. However, discrepancies between the model and actual site conditions, caused by either natural or human activities, can alter the surface morphology or introduce path obstructions. To address this challenge, the proposed framework divides the inspection task into: (a) generating the initial global view-plan for region of interests based on a historical map and (b) local view replanning to adapt to the current morphology of the inspection scene. The proposed hierarchy preserves global coverage objectives while enabling reactive adaptation to the local surface morphology. This enables the local autonomy to remain robust against environment uncertainty and complete the inspection tasks. We validate the approach through deployments in real-world subterranean mines using quadrupedal robot. A supplementary media highlighting the proposed method can be found here https://youtu.be/6TxK8S_83Lw.
