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Carnegie Mellon Robotics Institute

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Abstract

Accurately mapping the course and vegetation along a river is challenging, since overhanging trees block GPS at ground level and occlude the shore line when viewed from higher altitudes. We present a multimodal perception system for the active exploration and mapping of a river from a small rotorcraft. We describe three key components that use computer vision, laser scanning, inertial sensing and intermittant GPS to estimate the motion of the rotorcraft, de- tect the river without a prior map, and create a 3D map of the riverine environment. Our hardware and software approach is cognizant of the need to perform multi-kilometer missions below tree level with size, weight and power constraints. We present experimental results along a 2 km loop of river us- ing a surrogate perception payload. Overall we can build an accurate 3D obstacle map and a 2D map of the river course and width from light onboard sensing.

Keywords

3D obstacle mapping, Visual localization, Micro aerial vehicles, Self supervised learning, 3D ladar scanning

Notes

Associated Project(s): Riverine Mapping

Number of pages: 26

Text Reference

Sebastian Scherer, Joern Rehder, Supreeth Achar, Hugh Cover, Andrew D. Chambers, Stephen T. Nuske, and Sanjiv Singh, "River mapping from a flying robot: state estimation, river detection, and obstacle mapping," Autonomous Robots, Vol. 32, No. 5, May, 2012, pp. 1 - 26.

BibTeX Reference

@article{Scherer_2012_7040,
   author = "Sebastian Scherer and Joern Rehder and Supreeth Achar and Hugh Cover and Andrew D Chambers and Stephen T. Nuske and Sanjiv Singh",
   editor = "Gaurav Sukhatme",
   title = "River mapping from a flying robot: state estimation, river detection, and obstacle mapping",
   journal = "Autonomous Robots",
   pages = "1 - 26",
   publisher = "Springer",
   month = "May",
   year = "2012",
   volume = "32",
   number = "5",
}

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