Stereo vision for planetary rovers: stochastic modeling to near real-time implementation
International Journal of Computer Vision
Coordination for Multi-Robot Exploration and Mapping
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing
International Journal of Robotics Research
Traversable terrain classification for outdoor autonomous robots using single 2D laser scans
Integrated Computer-Aided Engineering - Informatics in Control, Automation and Robotics
DenseSLAM: Simultaneous Localization and Dense Mapping
International Journal of Robotics Research
Data Structures for Efficient Dynamic Processing in 3-D
International Journal of Robotics Research
Terrain traversability analysis methods for unmanned ground vehicles: A survey
Engineering Applications of Artificial Intelligence
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This paper addresses the problem of outdoor terrain modeling for the purposes of mobile robot navigation. We propose an approach in which a robot acquires a set of terrain models at differing resolutions. Our approach addresses one of the major shortcomings of Bayesian reasoning when applied to terrain modeling, namely artifacts that arise from the limited spatial resolution of robot perception. Limited spatial resolution causes small obstacles to be detectable only at close range. Hence, a Bayes filter estimating the state of terrain segments must consider the ranges at which that terrain is observed. We develop a multi-resolution approach that maintains multiple navigation maps, and derive rational arguments for the number of layers and their resolutions. We show that our approach yields significantly better results in a practical robot system, capable of acquiring detailed 3-D maps in large-scale outdoor environments.