The paper introduces a new approach (CBNNTAP) that addresses the complexities and challenges presented by ocean currents when optimizing target assignment and motion planning for a multi-unmanned underwater vehicle (UUV) system. The algorithm integrates several key components, including a bio-inspired neural network-based (BINN) approach, an efficient target assignment component, and an adjustment component to counteract the deviations caused by ocean currents. This enhances the accuracy of both motion planning and target assignment for the UUVs. The effectiveness of the CBNNTAP algorithm is demonstrated through comprehensive simulation results.
Publication date: 12 Jan 2024
Project Page: unknown
Paper: https://arxiv.org/pdf/2401.05521
