Parking Trajectory Planning Using Multiresolution State Roadmaps
Yuichi Tazaki, Hiroyuki Okuda, Tatsuya Suzuki · IEEE Transactions on Intelligent Vehicles · 2017
This paper presents a trajectory planning method for automated parking that makes use of multiresolution roadmaps. The proposed roadmap generation algorithm takes as an input manually designed geometric information of a parking lot consisting of parking space layout, obstacle configuration, and a set of geometric features called guidelines. It constructs a roadmap by dividing the guidelines in multiple resolutions until it achieves enough coverage over the set of safe trajectories satisfying vehicle kinematics, curvature limit, and collision-avoidance. Using this roadmap, a complex parking trajectory composed of both forward and reverse motions can be computed with small online computation cost. The proposed method is evaluated in both numerical simulations and real experiments.