Trajectory planning for automated parking using multi-resolution state roadmap considering non-holonomic constraints
Hiroshi Fuji, Jingyu Xiang, Yuichi Tazaki, Blaine Levedahl, Tatsuya Suzuki · 2014
This paper presents a trajectory planning method for automated parking. The proposed method constructs a state roadmap in which each node contains not only position but also orientation information of the vehicle. The roadmap is constructed by dividing the orientation space in multiple resolutions considering the non-holonomic constraints of the vehicle and the collision-avoidance constraints between the vehicle and the boundary of the parking environment. Using the state 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 an experiment using an electric vehicle.