Navigation in the Presence of Obstacles for an Agile Autonomous Underwater Vehicle
Navigation in the Presence of Obstacles for an Agile Autonomous Underwater Vehicle
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DOI：
10.1109/icra40945.2020.9197558
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发表时间：
2019-03
期刊：
影响因子：
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通讯作者：
M. Xanthidis;N. Karapetyan;Hunter Damron;S. Rahman;James Johnson;J. O’Kane;Ioannis M. Rekleitis
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文献类型：
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作者：
M. Xanthidis;N. Karapetyan;Hunter Damron;S. Rahman;James Johnson;J. O’Kane;Ioannis M. Rekleitis
水下航行传统上是通过与障碍物保持安全距离来完成的，从而导致感兴趣区域的“飞越”。自主水下航行器（AUV）在复杂空间（如沉船或装饰洞穴）中的运动是一个极具挑战性的问题，过去尚未解决。本文提出了一种新的导航框架，利用增强版的Trajopt的快速三维路径优化规划的AUV。基于采样的校正程序确保规划不受局部最小值的约束，从而能够在狭窄的空间中导航。提出了两种不同的模式：规划与已知的地图的结果在有效的轨迹通过杂乱的空间;在未知的环境中操作利用点云从视觉特征检测到有效地导航，同时避免检测到的障碍物。所提出的方法进行了严格的测试，无论是在模拟和在池中的实验，证明是足够快，使安全的实时三维自主导航的AUV。
Navigation underwater traditionally is done by keeping a safe distance from obstacles, resulting in "fly-overs" of the area of interest. Movement of an autonomous underwater vehicle (AUV) through a cluttered space, such as a shipwreck or a decorated cave, is an extremely challenging problem that has not been addressed in the past. This paper proposes a novel navigation framework utilizing an enhanced version of Trajopt for fast 3D path-optimization planning for AUVs. A sampling-based correction procedure ensures that the planning is not constrained by local minima, enabling navigation through narrow spaces. Two different modalities are proposed: planning with a known map results in efficient trajectories through cluttered spaces; operating in an unknown environment utilizes the point cloud from the visual features detected to navigate efficiently while avoiding the detected obstacles. The proposed approach is rigorously tested, both on simulation and in-pool experiments, proven to be fast enough to enable safe real-time 3D autonomous navigation for an AUV.