多自主水下航行器区域搜索与协同围捕方法研究

Research on Methods of Region Searching and Cooperative Hunting for Autonomous Underwater Vehicles

针对多个自主水下航行器(AUVs)执行区域搜索和协同围捕入侵对象的任务案例,设计了多航行器混合分层式体系结构,提出了分区域随机搜索策略和基于势点的优化围捕策略。将蚁群算法和人工势场法相结合,实现了AUVs路径规划与避碰。基于AUV六自由度运动模型和PID控制器,通过仿真实验验证了算法的有效性。仿真结果表明,AUVs具有在障碍环境中执行区域搜索和对入侵对象协同围捕的作业能力,设计的方法可应用于自主水下航行器的围捕任务。

In allusion to a given case in which some autonomous underwater vehicles（AUVs for short） are used to carry out the task of region searching and cooperative hunting for an invasive target,a hybrid hierarchical architecture is designed in the paper.A regional random searching strategy and an optimal stalking strategy based on the idea of ＂potential point＂ are presented as well.Furthermore,ant colony optimization algorithm（ACO） and virtual-field-force method are combined and applied to solve the problem of path planning and obstacle avoiding.Based on the existing six-freedom dynamic model of AUV and a PID controller,some simulating tests are done to inspect and verify the validation of the research method.The simulating results show that AUVs have the ability to fulfill the task of region searching and cooperative hunting for an invasive target in an environment with some obstacles.