基于因子图的USV集群协同导航算法

2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) Pub Date : 2022-10-03 DOI:10.1109/IAEAC54830.2022.9929590

Jianwei Liu, Hao Guo, Xixiang Liu, S. Pan

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引用次数: 0

摘要

协同导航是无人水面飞行器(USV)集群执行任务必须解决的关键技术之一。采用分散式解耦结构，利用USV自身雷达或光电传感器测量USV之间的相对距离和相对方位，建立基于因子图的协同导航算法，实现USV集群的高精度协同定位。采用Lora自组织网络实现usv间测量信息的共享。通过USV集群的导航实验，结果表明该算法可以提高低导航精度USV的协同定位精度。

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USV Cluster Cooperative Navigation Algorithm based on factor graph

Cooperative navigation is one of the critical technologies that must be tackled for Unmanned surface vehicle(USV) clusters to perform missions. It adopts decentralized decoupling structure and uses USV's own radar or photoelectric sensors to measure the relative distance and relative azimuth between USVs, and establishes a factor graph-based cooperative navigation algorithm to achieve high-precision cooperative positioning of USV clusters. Lora ad hoc network is used to realize the sharing of measurement information between USVs. Through the navigation experiments of USV clusters, the results show that the algorithm can improve the accuracy of cooperative positioning of low navigation accuracy USVs.

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2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )

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