基于并行进化算法的多无人水面艇快速协同航迹规划OA
Multi-USV Fast Cooperative Path Planning Based on Parallel Evolutionary Algorithms
多艘无人水面艇(USV)协同作战是未来战争的重要发展趋势,快速协同航迹规划将使协同作战成为可能.针对现有航迹规划方法在协同性和快速性难以兼顾,导致搜索效率低、协同约束处理复杂等问题,首先在基于 Voronoi 图的规划空间模型上给出了初始航迹表达形式,根据约束条件计算出初始航迹代价,完成了基于 Voronoi 图的初始航迹生成.然后应用并行计算技术优化进化算法对初始航迹进行搜索,设计了单艇快速航迹规划方法.最后结合 USV 多艇协同控制策略,给出了满足约束条件的协同航迹.仿真结果表明,该算法应用在多艇协同航迹规划中能快速有效地规划出最优航迹,与传统遗传算法相比进化代数降低了约 40%,进化时间减少了约 53%.
Cooperative combat involving multiple unmanned surface vehicles(USVs)is an important development trend in future warfare,and rapid cooperative path planning will make cooperative combat possible.To address issues such as the low search efficiency and overly complicated coordination constraints of existing path planning methods caused by the difficulty in balancing coordination and speed,an initial path expression form is given based on the Voronoi diagram planning space model,the initial path cost is calculated according to the constraints,and the initial path generation process is completed based on the Voronoi diagram.Then,an evolutionary algorithm utilizing parallel computing technology is applied to search for the initial path,and a rapid path planning method for single USV is designed.Finally,combined with the multi-USV cooperative control strategy,a cooperative path that meets the constraints is provided.Simulation results show that rapid,efficient,and optimal multi-USV cooperative path planning can be realized using this algorithm.Compared with the traditional genetic algorithm,the number of evolution generations is reduced by approximately 40%,and the evolution time is decreased by about 53%.
郑伟伟;曹璐
中国船舶集团有限公司工程管理中心 北京 100192宜昌测试技术研究所,湖北 宜昌 443003
信息技术与安全科学
并行计算进化算法动态决策协同约束航迹规划
parallel computingevolutionary algorithmdynamic decision-makingcollaborative constraintspath planning
《数字海洋与水下攻防》 2026 (2)
208-214,7
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