Autonomous driving in semi-structured environments: Mapping and planning
- 1 May 2009
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 3407-3414
- https://doi.org/10.1109/robot.2009.5152682
Abstract
We consider the problem of autonomous driving in semi-structured environments (e.g., parking lots). Such environments have strong topological structure (graphs of drivable lanes), but maneuvers with significant deviations from those graphs are valid and frequent. We address two main challenges of operating in such environments: i) detection of topological structure from sensor data, and ii) using that structure to guide path planning. We present experimental results on both of these topics, demonstrating robust estimation of lane networks in parking lots and the benefits of using these topological networks to guide path planning.Keywords
This publication has 11 references indexed in Scilit:
- Junior: The Stanford entry in the Urban ChallengeJournal of Field Robotics, 2008
- Planning Long Dynamically-Feasible Maneuvers For Autonomous VehiclesPublished by Robotics: Science and Systems Foundation ,2008
- Discrete Search Leading Continuous Exploration for Kinodynamic Motion PlanningPublished by Robotics: Science and Systems Foundation ,2007
- Autonomous Driving in Structured and Unstructured EnvironmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- High-speed navigation using the global dynamic window approachPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- A complete navigation system for goal acquisition in unknown environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Recent progress in local and global traversability for planetary roversPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Automated Highways and the Free Agent DemonstrationPublished by Springer Science and Business Media LLC ,1998
- Probabilistic roadmaps for path planning in high-dimensional configuration spacesIEEE Transactions on Robotics and Automation, 1996
- Optimal paths for a car that goes both forwards and backwardsPacific Journal of Mathematics, 1990