Adaptive adjustable fast marching square method based path planning for the swarm of heterogeneous unmanned surface vehicles (USVs). (15th January 2023)

• Record Type: Journal Article
• Authors: Tan, Guoge; Zhuang, Jiayuan; Zou, Jin; Wan, Lei
• Is Part Of: Ocean engineering. Volume 268(2023)
• Publication Date: 2023-01-15
• Subjects: Heterogeneous USVs -- USV swarm -- Path planning -- Fast marching square method; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.113432
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: In the process of deploying multiple unmanned surface vehicles (USVs) to work collaboratively, path planning is s an essential component. A team of USVs that perform joint missions, may have heterogeneity in the draft, endurance, dynamic characteristics, etc. If the path planning for each USV in the swarm is carried out separately, it is not only time-consuming but also difficult to ensure the unity of the entire swarm. So, a path planning method for the whole swarm is studied herein and how to take the aforesaid heterogeneities of USVs into consideration during the path planning is the main focus of the paper. The unified motion model of the heterogeneous USV swarm and the model representing the heterogeneities of USVs are given firstly, which is the baseline of the following content. Then, the fundamental of the fast marching square (FMS) method is elaborated, and the cutoff threshold function Sat( x ) is added to the FMS method to adjust the potential field of the FMS so that different paths can be obtained. The adaptive adjustable fast marching square (AAFMS) method is proposed later, and its core idea is to adjust the potential field of the FMS to generate the desired path that meets the needs of heterogeneous USVs. Afterwards, the potential field is adjusted further to make the planned path comply with the International Regulations for Preventing Collisions at Sea (COLREGs), which also improves the applicability of the proposed path planning method in practical applications. Comparative simulation results demonstrate the effectiveness of the proposed method. Highlights: A novel unified 3-DOF motion model is established for the USV swarm of heterogeneous USVs. An evaluation function is proposed to evaluate the fitness of planned paths corresponding to USVs' heterogeneities. The anisotropy is introduced into the FMS-based method to adjust the potential field according to USVs' heterogeneities. The FMS-based method is improved to make the path planning meet the requirements of the COLREGs.