Motion planning in urban environments: Part I
- 1 September 2008
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1063-1069
- https://doi.org/10.1109/iros.2008.4651120
Abstract
We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultra-reliability, high-speed operation, complex inter-vehicle interaction, parking in large unstructured lots, and constrained maneuvers. Our approach combines a model-predictive trajectory generation algorithm for computing dynamically-feasible actions with two higher-level planners for generating long range plans in both on-road and unstructured areas of the environment. In this Part I of a two-part paper, we describe the underlying trajectory generator and the on-road planning component of this system. We provide examples and results from ldquoBossrdquo, an autonomous SUV that has driven itself over 3000 kilometers and competed in, and won, the Urban Challenge.Keywords
This publication has 5 references indexed in Scilit:
- Detection, prediction, and avoidance of dynamic obstacles in urban environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- Optimal Rough Terrain Trajectory Generation for Wheeled Mobile RobotsThe International Journal of Robotics Research, 2007
- Global Path Planning on Board the Mars Exploration RoversPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- Recent progress in local and global traversability for planetary roversPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A complete navigation system for goal acquisition in unknown environmentsAutonomous Robots, 1995