摘要
面向海空无人编组高效反水雷的任务需求,提出了一种雷区最优覆盖规划算法.该算法利用无人机探雷编组的速度优势对重点水域进行侦察,并应用高斯过程回归求得水雷分布态势,结合无人艇速度权重设计代价函数,对雷区进行了最优划分,以提高作业效率.进一步考虑无人艇的欠驱动运动学模型对覆盖问题的影响,设计运动规划算法引导无人艇向其主导区域内的最优位置移动,充分利用无人艇编组机动能力,使灭雷任务完成时间最优.通过仿真实验比较所提算法与基线算法,验证所提出算法在反水雷效率方面的优势.
To meet the task requirements for efficient anti-mine task by sea-air unmanned formation,an optimal coverage planning algorithm in mine area is proposed.The algorithm utilizes the speed advantage of UAV mine detection formation to detect on the key water area.Gaussian process regression is applied to obtain mine distribution situation.Meanwhile,a cost function is designed based on speed-weight of unmanned surface vessels for optimal division on the mine zone so as to improve the operation efficiency.The influence of under-actuated kinematic model of unmanned surface vessels on the coverage problem is further considered,the motion planning algorithm is designed to guide the unmanned surface vessels to move to the optimal position in dominant region.The maneuverability of unmanned surface vessel formation is made full use of to make time optimal of mine destruction.Finally,the proposed algorithm is compared with baseline algorithm by simulation and experiment,the advantage of the proposed algorithm in the anti-mine efficiency is verified.
作者
张嘉玲
姜永超
李博宸
王成罡
宋磊
黄丹
ZHANG Jialing;JIANG Yongchao;LI Bochen;WANG Chenggang;SONG Lei;HUANG Dan(School of Aeronautics and Astronautics,Shanghai Jiao Tong University,Shanghai 200240,China;School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《指挥与控制学报》
CSCD
2023年第4期469-477,共9页
Journal of Command and Control
基金
上海交通大学深蓝计划(SL2022MS010,SL2022MS008)
装备预研教育部联合基金(8091B022235)
国防科技重点实验室基金(2022JCJQLB03308)资助。
关键词
高斯过程回归
时间最优覆盖
速度差异性
海空协同
欠驱动无人艇
gaussian process regression
time-optimal coverage
speed difference
sea-air coordination
under-actuated unmanned surface vessel
