Planning with uncertainty in position using high-resolution maps
Planning with uncertainty in position using high-resolution maps
LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information
International Journal of Robotics Research
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This paper presents two new approaches that enable the use of linear landmarks for planning paths with uncertainty in position in outdoor environments. The first approach uses a combination of forward simulation and entropy to reduce the dimensionality of the search space, while still preserving most of the information required to propagate a full covariance matrix. The second approach adds incremental binning to improve the quality of the solution while still keeping the dimensionality of the search space relatively low. These approaches provide a better compromise of speed and quality of the solution than most existing approaches, and are able to successfully utilize linear landmarks in large outdoor environments.