Title :
Motion planning for urban driving using RRT
Author :
Kuwata, Yoshiaki ; Fiore, Gaston A. ; Teo, Justin ; Frazzoli, Emilio ; How, Jonathan P.
Author_Institution :
Dept. of Aeronaut. & Astronaut., Massachusetts Inst. of Technol., Cambridge, MA
Abstract :
This paper provides a detailed analysis of the motion planning subsystem for the MIT DARPA Urban Challenge vehicle. The approach is based on the Rapidly-exploring Random Trees (RRT) algorithm. The purpose of this paper is to present the numerous extensions made to the standard RRT algorithm that enable the on-line use of RRT on robotic vehicles with complex, unstable dynamics and significant drift, while preserving safety in the face of uncertainty and limited sensing. The paper includes numerous simulation and race results that clearly demonstrate the effectiveness of the planning system.
Keywords :
mobile robots; path planning; tree searching; MIT DARPA Urban Challenge vehicle; motion planning; rapidly-exploring random trees algorithm; robotic vehicles; urban driving; Heuristic algorithms; Meteorology; Planning; Roads; Robots; Trajectory; Vehicles;
Conference_Titel :
Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on
Conference_Location :
Nice
Print_ISBN :
978-1-4244-2057-5
DOI :
10.1109/IROS.2008.4651075