The paper presents the CBNNTAP algorithm, an innovative approach to optimize target assignment and motion planning for a multi-unmanned underwater vehicle (UUV) system. The algorithm incorporates a bio-inspired neural network-based (BINN) approach for path prediction and collision avoidance. It also integrates an efficient target assignment component and an adjustment component to counteract deviations caused by ocean currents. The effectiveness of the CBNNTAP algorithm is tested through simulations and the results show its superiority in nullifying the effects of static and dynamic ocean currents in 2D and 3D scenarios.
Publication date: 12 Jan 2024
Project Page: Not provided
Paper: https://arxiv.org/pdf/2401.05521
