The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

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",
}

The Robotics Institute

Menu