Geomagnetic Perceiving Navigation Method for Autonomous Underwater Vehicle Using an Adapted Search Strategy

摘要

This paper proposes an adapted search strategy to solve the optimization searching problem of geomagnetic perceiving navigation for autonomous underwater vehicle. The activation rule for agent is to dynamically allocate the regulating commands among various environments. Therefore, the activation rule for autonomous underwater vehicle is vital to ensure the overall searching performance. In this paper, the activation rule is applied to provide an interactive self-learning to minimize the cost function. It can become an effective learning model for search strategy in the geomagnetic perceiving navigation. At last, the proposed adapted motion search algorithm is implemented and the results can show the reliability and effectiveness of the proposed algorithm.