Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Alice: An information-rich autonomous vehicle for high-speed desert navigation: Field Reports
Journal of Robotic Systems - Special Issue on the DARPA Grand Challenge, Part 2
An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing
International Journal of Robotics Research
Monte Carlo localization in outdoor terrains using multilevel surface maps
Journal of Field Robotics - Special Issue on Field and Service Robotics
Junior: The Stanford entry in the Urban Challenge
Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part II
Theta*: any-angle path planning on grids
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
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Recently, the problem of autonomous navigation of automobiles has gained substantial interest in the robotics community. Especially during the two recent DARPA grand challenges, autonomous cars have been shown to robustly navigate over extended periods of time through complex desert courses or through dynamic urban traffic environments. In these tasks, the robots typically relied on GPS traces to follow pre-defined trajectories so that only local planners were required. In this paper, we present an approach for autonomous navigation of cars in indoor structures such as parking garages. Our approach utilizes multi-level surface maps of the corresponding environments to calculate the path of the vehicle and to localize it based on laser data in the absence of sufficiently accurate GPS information. It furthermore utilizes a local path planner for controlling the vehicle. In a practical experiment carried out with an autonomous car in a real parking garage we demonstrate that our approach allows the car to autonomously park itself in a large-scale multi-level structure.