Abstract-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.
R. Kümmerle and W. Burgard REF developed an autonomous system that utilizes multi-level surface maps of corresponding environments to localize itself based on the particle filter.
Autonomous driving in a multi-level parking structure
2009 IEEE International Conference on Robotics and Automation
2009 IEEE International Conference on Robotics and Automation
Engineering Computer Science