Local Path Planning of Unmanned Surface Vehicles’ Formation Based on Vector Field and Flow Field Traction

Formation obstacle avoidance is an essential attribute of the cooperative task in unmanned surface vehicle (USV) formation. In real-world scenarios involving multiple USVs, both formation obstacle avoidance and formation recovery after obstacle avoidance play a critical role in ensuring the success of collaborative missions. In this study, an Interfered Fluid Dynamic System (IFDS) algorithm was used for obstacle avoidance due to its excellent robustness, high computational efficiency and path smoothness. The algorithm can provide good local path planning for USVs. However, the use of the IFDS on USVs still has the defect of local extreme values, which has been effectively modified to obtain an enhanced IFDS (EIFDS). In formation, based on the leader–follower method, the virtual leader was used to determine the desired position of USVs in formation, and the streamlines generated by the EIFDS guided the USVs. In order to make the formation converge to the desired formation better, the vector and scalar of the EIFDS algorithm were uncoupled, and different designs were made to achieve convergence to the desired formation. The interfered residue of the IFDS is not suitable for addressing collision avoidance between USVs in practice. Therefore, the vector field method was employed to tackle the issue, with some enhancements made to optimize its performance. Subsequently, a weighted separation method was applied to combine the vector field and EIFDS, resulting in a composite field solution. Finally, the formation obstacle avoidance strategy based on composite fields was formed. The feasibility of this scheme was verified by simulation, and compared with the single IFDS formation method, the pairwise spacing of USVs behind obstacles could be increased, and the reliability of formation obstacle avoidance was increased.