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

Sampling in the space of controls or actions is a well-established method for ensuring feasible local motion plans. However, as mobile robots advance in performance and competence in complex environments, this classical motion-planning technique ceases to be effective. When environmental constraints severely limit the space of acceptable motions or when global motion planning expresses strong preferences, a state space sampling strategy is more effective. Although this has been evident for some time, the practical question is how to achieve it while also satisfying the severe constraints of vehicle dynamic feasibility. The paper presents an effective algorithm for state space sampling utilizing a model-based trajectory generation approach. This method enables high-speed navigation in highly constrained and/or partially known environments such as trails, roadways, and dense off-road obstacle fields.

Notes

Associated Center(s) / Consortia: National Robotics Engineering Center and Field Robotics Center

Associated Project(s): Urban Challenge, UGCV PerceptOR Integrated, Tartan Racing

Number of pages: 21

Text Reference

Thomas Howard, Colin Green, David Ferguson, and Alonzo Kelly, "State Space Sampling of Feasible Motions for High-Performance Mobile Robot Navigation in Complex Environments," Journal of Field Robotics, Vol. 25, No. 6-7, June, 2008, pp. 325-345.

BibTeX Reference

@article{Howard_2008_6171,
   author = "Thomas Howard and Colin Green and David Ferguson and Alonzo Kelly",
   title = "State Space Sampling of Feasible Motions for High-Performance Mobile Robot Navigation in Complex Environments",
   journal = "Journal of Field Robotics",
   pages = "325-345",
   publisher = "Wiley Periodicals, Inc.",
   month = "June",
   year = "2008",
   volume = "25",
   number = "6-7",
}

The Robotics Institute

Menu