River mapping from a flying robot: state estimation, river detection, and obstacle mapping
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 intermittent GPS to estimate the motion of the rotorcraft, detect 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 using 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.
BibTeX
@article{Scherer-2012-7472,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},
}