期刊
AUTONOMOUS ROBOTS
卷 33, 期 1-2, 页码 189-214出版社
SPRINGER
DOI: 10.1007/s10514-012-9293-0
关键词
3D obstacle mapping; Visual localization; Micro aerial vehicles; Self supervised learning; 3D ladar scanning
资金
- Office of Naval Research [N00014-10-1-0715]
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, 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.
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