Riverine Coverage with an Autonomous Surface Vehicle over Known Environments

Nare Karapetyan, Adam Braude, Jason Moulton, Joshua A. Burstein, Scott White, Jason O'Kane, Ioannis Rekleitis
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019.

Abstract

Abstract: — Environmental monitoring and surveying operations on rivers currently are performed primarily with manually-operated boats. In this domain, autonomous coverage of areas is of vital importance, for improving both the quality and the efficiency of coverage. This paper leverages human expertise in river exploration and data collection strategies to automate and optimize these processes using autonomous surface vehicles (ASVs). In particular, three deterministic algorithms for both partial and complete coverage of a river segment are proposed, providing varying path length, coverage density, and turning patterns. These strategies resulted in increases in accuracy and efficiency compared to human performance. The proposed methods were extensively tested in simulation using maps of real rivers of different shapes and sizes. In addition, to verify their performance in real world operations, the algorithms were deployed successfully on several parts of the Congaree River in South Carolina, USA, resulting in total of more than 35km of coverage trajectories in the field.

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BibTeX

@inproceedings{KarapetyanIROS2019,
  author       = {Nare Karapetyan and Adam Braude and Jason Moulton and
		 Joshua A. Burstein and Scott White and Jason O'Kane and
		 Ioannis Rekleitis},
  title        = {{Riverine Coverage with an Autonomous Surface Vehicle
		 over Known Environments}},
  booktitle    = {IEEE/RSJ International Conference on Intelligent Robots
		 and Systems (IROS)},
  year	       = {2019},
  pages        = {(accepted)},
  month        = {Nov.},
  address      = {Macau}
}

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Wed Sep 18 06:21:01 EDT 2019