Algorithm Design of Perception and Navigation for Unmanned Vehicles Based on Multi-Sensor Fusion and Co- Location
Lan Ban, Can Yang, Junpei Liu, Huan Chi, Hongfeng Zhang · 2023
Aiming at the perception and navigation problems of unmanned vehicles, this paper designs a perception and navigation algorithm based on multi-sensor fusion and cooperative positioning. The algorithm realizes the perception of the environment through multi-sensor fusion technology, and at the same time realizes the high-precision positioning of unmanned vehicles by using collaborative positioning technology. On this basis, the fused data is optimized using a state-space model, which improves the accuracy of perception and navigation results. In order to verify the algorithm proposed in the article, an experimental test was carried out on an unmanned vehicle. The test results show that the perception and navigation algorithm designed in this article can increase the perception accuracy to a maximum of 96.8%, and can also effectively improve the positioning accuracy and communication efficiency, and can reduce the collision accidents caused by the vehicle entering the obstacle area by mistake.