未知の不整地におけるリスクフリー自律ナビゲーションのための履歴考慮型プランニング
History-Aware Planning for Risk-free Autonomous Navigation on Unknown Uneven Terrain
不整地を含む未知環境で地図なしに自律移動するため、探索履歴を保持する階層構造を用いて危険領域を明示的に特定し、安全かつ迅速に目標へ到達するナビゲーション手法を提案した。
著者: Yinchuan Wang, Nianfei Du, Yongsen Qin, Xiang Zhang, Rui Song, Chaoqun Wang
分類: cs.RO
原文アブストラクト
It is challenging for the mobile robot to achieve autonomous and mapless navigation in the unknown environment with uneven terrain. In this study, we present a layered and systematic pipeline. At the local level, we maintain a tree structure that is dynamically extended with the navigation. This structure unifies the planning with the terrain identification. Besides, it contributes to explicitly identifying the hazardous areas on uneven terrain. In particular, certain nodes of the tree are consistently kept to form a sparse graph at the global level, which records the history of the exploration. A series of subgoals that can be obtained in the tree and the graph are utilized for leading the navigation. To determine a subgoal, we develop an evaluation method whose input elements can be efficiently obtained on the layered structure. We conduct both simulation and real-world experiments to evaluate the developed method and its key modules. The experimental results demonstrate the effectiveness and efficiency of our method. The robot can travel through the unknown uneven region safely and reach the target rapidly without a preconstructed map.
