Ocean front detection and tracking using a team of heterogeneous marine vehicles
Ocean front detection and tracking using a team of heterogeneous marine vehicles
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使用一组不同种类的海洋车辆进行海洋前沿探测和跟踪
DOI：
10.1002/rob.22014
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发表时间：
2021-01
影响因子：
8.3
通讯作者：
Seth McCammon;Gilberto Marcon dos Santos;M. Frantz;T. Welch;Graeme Best;R. Shearman;J. Nash;J. Barth;J. Adams;Geoffrey A. Hollinger
中科院分区：
文献类型：
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作者：
Seth McCammon;Gilberto Marcon dos Santos;M. Frantz;T. Welch;Graeme Best;R. Shearman;J. Nash;J. Barth;J. Adams;Geoffrey A. Hollinger
海洋监测是一项昂贵且耗时的奋进，但可以通过使用自主机器人团队来提高效率。在本文中，我们提出了一个系统的自主识别和跟踪的海洋锋，通过协调的一个异质团队的自主水面车辆（ASV）和自主水下航行器（AUV）的采样工作。这项研究的主要贡献是（1）我们的算法，用于执行自治协调使用一般自治原则：序贯分配蒙特卡罗树搜索（SA-MCTS），通过使用最近邻先验增强标准高斯过程和在漂移参考系中进行规划，将领域知识纳入环境估计，（2）我们的决策支持用户界面，以帮助人类操作员监督自主系统，以及（3）在墨西哥湾为期2周的部署中，使用由4架斯洛克姆滑翔机和2架机器人海洋表面采样器组成的异质团队演示系统的操作。通过这些贡献，我们的目标是弥合最先进的自主算法和已经在大规模现场试验中测试的海上车辆规划方法之间的差距。本文提出了第一次部署的一般，启发式的，多机器人协调算法的扩展采样使命。
Ocean monitoring is an expensive and time consuming endeavor, but it can be made more efficient through the use of teams of autonomous robots. In this paper, we present a system for the autonomous identification and tracking of ocean fronts by coordinating the sampling efforts of a heterogeneous team of autonomous surface vehicles (ASVs) and autonomous underwater vehicles (AUVs). The primary contributions of this study are (1) our algorithm for performing autonomous coordination using general autonomy principles: Sequential Allocation Monte Carlo Tree Search (SA‐MCTS) which incorporates domain knowledge into the environmental estimation through both augmenting a standard Gaussian process with a nearest neighbors prior and planning in a drifting reference frame, (2) our decision support user interface to help human operators oversee the autonomous system, and (3) the demonstration of the system's operation in a 2‐week long deployment in the Gulf of Mexico using a heterogeneous team of four Slocum gliders and two robotic ocean surface samplers. With these contributions, we aim to bridge the gap between state of the art autonomy algorithms and marine vehicle planning methods that have been tested in large‐scale field trials. This paper presents the first deployment of a general, heuristic‐based, multi‐robot coordination algorithm for an extended sampling mission.