AAAI Publications, Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence

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A Travel-Time Optimizing Edge Weighting Scheme for Dynamic Re-Planning
Andrew Feit, Lenrik Toval, Raffi Hovagimian, Rachel Greenstadt

Last modified: 2010-07-07


The success of autonomous vehicles has made path planning in real, physically grounded environments an increasingly important problem. In environments where speed matters and vehicles must maneuver around obstructions, such as autonomous car navigation in hostile environments, the speed with which real vehicles can traverse a path is often dependent on the sharpness of the corners on the path as well as the length of path edges. We present an algorithm that incorporates the use of the turn angle through path nodes as a limiting factor for vehicle speed. Vehicle speed is then used in a time-weighting calculation for each edge. This allows the path planning algorithm to choose potentially longer paths, with less turns in order to minimize path traversal time. Results simulated in the Breve environment show that travel time can be reduced over the solution obtained using the Anytime D* Algorithm by approximately 10% for a vehicle that is speed limited based on turn rate.


motion planning; navigation; graph planning

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