不整備環境における3Dリアクティブ制御とフロンティア探索
3D Reactive Control and Frontier-Based Exploration for Unstructured Environments
地図と深度センサ情報を併用する2層計画で、フロンティア探索と人工ポテンシャル法により障害物の多い倉庫内をドローンが自律航行する手法を提案・実証した。
著者: Shakeeb Ahmad, Andrew B. Mills, Eugene R. Rush, Eric W. Frew, J. Sean Humbert
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
The paper proposes a reliable and robust planning solution to the long range robotic navigation problem in extremely cluttered environments. A two-layer planning architecture is proposed that leverages both the environment map and the direct depth sensor information to ensure maximal information gain out of the onboard sensors. A frontier-based pose sampling technique is used with a fast marching cost-to-go calculation to select a goal pose and plan a path to maximize robot exploration rate. An artificial potential function approach, relying on direct depth measurements, enables the robot to follow the path while simultaneously avoiding small scene obstacles that are not captured in the map due to mapping and localization uncertainties. We demonstrate the feasibility and robustness of the proposed approach through field deployments in a structurally complex warehouse using a micro-aerial vehicle (MAV) with all the sensing and computations performed onboard.
