摘要
针对水面无人艇在复杂多变的海洋环境下,其航迹实时规划难度较大的问题,提出了一种基于简单模型的无人艇航迹规划算法。根据由电子海图获得的静态障碍物信息,建立航行海区的全局静态环境模型,再利用粒子群优化算法进行全局航迹规划得到参考航迹;当无人艇沿着参考航迹航行时,建立基于雷达探测的局部动态威胁模型,并按提出的动态威胁规避策略实时调整航行轨迹。仿真结果验证了该算法的可行性,提高了水面无人艇对海洋环境的适应性,可得到比较理想的航迹路线。
Aimed at the difficulty of real-time path planning for unmanned surface vehicle（USV） under complex and variable marine environment, a simple model-based algorithm was presented to solve the problem of USV path planning. According to the static obstacle information obtained from the electronic chart, the global static environment model of the sea area was established, then the reference path was obtained by using the particle swarm optimization（PSO） algorithm. When USV sails along the reference path, a local dynamic threat model based on radar detection is established, and the path is adjusted in real-time as the proposed dynamic threat mitigation strategy. The simulation results show that the algorithm can obtain the ideal path planning and improve the environment adaptability of the USV.
出处
《武汉理工大学学报》
CAS
北大核心
2016年第6期84-88,共5页
Journal of Wuhan University of Technology
基金
湖北省自然科学基金(2015CFB586
2016CFB502)
中央高校基本科研业务费专项资金(163111005)
