River mapping from a flying robot: state estimation, river detection, and obstacle mapping

Sebastian Scherer, Joern Rehder, Supreeth Achar, Hugh Cover, Andrew D. Chambers, Stephen T. Nuske and Sanjiv Singh
Journal Article, Autonomous Robots, Vol. 32, No. 5, pp. 189 – 214, May, 2012

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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.

author = {Sebastian Scherer and Joern Rehder and Supreeth Achar and Hugh Cover and Andrew D. Chambers and Stephen T. Nuske and Sanjiv Singh},
title = {River mapping from a flying robot: state estimation, river detection, and obstacle mapping},
journal = {Autonomous Robots},
year = {2012},
month = {May},
volume = {32},
number = {5},
pages = {189 – 214},
keywords = {3D obstacle mapping, Visual localization, Micro aerial vehicles, Self supervised learning, 3D ladar scanning},
} 2018-10-04T11:19:09-04:00