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RI | Publications | Planning with Uncertainty in Position: An Optimal and Efficient Planner
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Planning with Uncertainty in Position: An Optimal and Efficient Planner
J.P. Gonzalez and A. Stentz
Proceedings of the IEEE International
Conference on Intelligent Robots and Systems (IROS '05), August, 2005, pp. 2435 - 2442.
Jump to: Download | Abstract | Notes | Text Reference | BibTeX Reference
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| Abstract |
We introduce a resolution-optimal path planner that considers uncertainty while optimizing any monotonic objective function such as mobility cost, risk, or energy expended. The resulting path minimizes the expected cost of the objective function, while ensuring that the uncertainty in the position of the robot does not compromise the safety of the robot or the reachability of the goal. Although the problem domain is stochastic in nature, our algorithm takes advantage of deterministic path-planning techniques to achieve significant performance improvements.
| Notes |
Associated centers: VASC and FRC
Associated lab/group: NavLab
Associated project: CTA Robotics
Number of pages: 8
| Text Reference |
J.P. Gonzalez and A. Stentz, "Planning with Uncertainty in Position: An Optimal and Efficient Planner," Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS '05), August, 2005, pp. 2435 - 2442.
| BibTeX Reference |
@inproceedings{Gonzalez_2005_5155,
author = "Juan Pablo Gonzalez and Anthony (Tony) Stentz",
title = "Planning with Uncertainty in Position: An Optimal and Efficient Planner",
booktitle = "Proceedings of the IEEE International
Conference on Intelligent Robots and Systems (IROS '05)",
month = "August",
year = "2005",
pages = "2435 - 2442"
}