Obstacle detection for lake-deployed autonomous surface vehicles using RGB imagery
We describe and test an obstacle-detection system for small, lake-deployed autonomous surface vehicles (ASVs) that relies on a low-cost, consumer-grade camera and runs on a single-board computer. A key feature of lakes that must be accounted for is the frequent presence of the shoreline in images as...
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Veröffentlicht in: | PloS one 2018-10, Vol.13 (10), p.e0205319-e0205319 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We describe and test an obstacle-detection system for small, lake-deployed autonomous surface vehicles (ASVs) that relies on a low-cost, consumer-grade camera and runs on a single-board computer. A key feature of lakes that must be accounted for is the frequent presence of the shoreline in images as well as the land-sky boundary. These particularities, along with variable weather conditions, result in a wide range of scene variations, including the possible presence of glint. The implemented algorithm is based on two main steps. First, possible obstacles are detected using an innovative gradient-based image processing algorithm developed especially for a camera with a low viewing angle to the water (i.e., the situation for a small ASV). Then, true and false positives are differentiated using correlation-based multi-frame analysis. The algorithm was tested extensively on a small ASV deployed in Lake Geneva. Under operational conditions, the algorithm processed 640×480-pixel images from a Raspberry Pi Camera at about 3-4 Hz on a Raspberry Pi 3 Model B computer. The present algorithm demonstrates that single-board computers can be used for effective and low-cost obstacle detection systems for ASVs operating in variable lake conditions. |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0205319 |