Path planning for autonomous ships

Path planning for autonomous ships: A hybrid approach based on improved apf and modified vo methods

Zhang, Liang (Wuhan University of Technology; Hubei Key Laboratory of Inland Shipping Technology)
Mou, Junmin (Wuhan University of Technology; Hubei Key Laboratory of Inland Shipping Technology)
Chen, Pengfei (Wuhan University of Technology; Hubei Key Laboratory of Inland Shipping Technology)
Li, M. (TU Delft Safety and Security Science; Wuhan University of Technology; Hubei Key Laboratory of Inland Shipping Technology)

2021

In this research, a hybrid approach for path planning of autonomous ships that generates both global and local paths, respectively, is proposed. The global path is obtained via an improved artificial potential field (APF) method, which makes up for the shortcoming that the typical APF method easily falls into a local minimum. A modified velocity obstacle (VO) method that incorpo-rates the closest point of approach (CPA) model and the International Regulations for Preventing Collisions at Sea (COLREGS), based on the typical VO method, can be used to get the local path. The contribution of this research is two-fold: (1) improvement of the typical APF and VO methods, making up for previous shortcomings, and integrated COLREGS rules and good seamanship, making the paths obtained more in line with navigation practice; (2) the research included global and local path planning, considering both the safety and maneuverability of the ship in the process of avoiding collision, and studied the whole process of avoiding collision in a relatively entirely way. A case study was then conducted to test the proposed approach in different situations. The results indicate that the proposed approach can find both global and local paths to avoid the target ship.

Artificial potential field method
Autonomous ship
Path planning
Velocity obstacles method

http://resolver.tudelft.nl/uuid:8a59f5fd-bf25-4c01-9019-0cf747672255

https://doi.org/10.3390/jmse9070761

2077-1312

Journal of Marine Science and Engineering, 9 (7)

Institutional Repository

journal article

© 2021 Liang Zhang, Junmin Mou, Pengfei Chen, M. Li