Planning with Uncertainty in Position: An Optimal and Efficient Planner

Juan Pablo Gonzalez and Anthony (Tony) Stentz
Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS '05), August, 2005, pp. 2435 - 2442.


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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.

Keywords
mobile robot, path planning, uncertainty, optimal planner, error propagation

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Field Robotics Center
Associated Project(s): CTA Robotics
Number of pages: 8

Text Reference
Juan Pablo Gonzalez and Anthony (Tony) 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)",
   pages = "2435 - 2442",
   month = "August",
   year = "2005",
}