Research on grid data generation technology for field path planning of armored vehicles

Yan Cui; Kaifeng Zheng; Pu Li

doi:10.1117/12.2654062

27 September 2022 Research on grid data generation technology for field path planning of armored vehicles

Yan Cui, Kaifeng Zheng, Pu Li

Proceedings Volume 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022); 123460Q (2022) https://doi.org/10.1117/12.2654062
Event: 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 2022, Kunming, China

Abstract

To address the lack of effective models and data in field combat path planning and position planning of armored vehicles, and to solve the slow real-time calculation speed due to the high precision and large data volume, an overall correction method is proposed targeting the strong coupling relationship between field environment characteristics and vehicle maneuverability. Based on this idea, a vehicle passing probability model under different layer data is constructed with the known field elevation data, vector data, and the maneuvering parameters of the reference vehicle. This model produces a grid of passing probability for each layer, and then weights and sums the passing probabilities of all layers to obtain the comprehensive probability of the whole area. In addition, this paper performs a three-level buffer calculation on the road layer, which generates different passing probabilities in the outer layer, the middle layer, and the inner layer. The calculation method effectively avoids the typical problem of A* path planning, which is prone to producing path results closing to the edge of the obstacles; for the situation where multiple geometric elements of a layer occupy one grid at the same time, the passing probability of the grid is comprehensively calculated through the area proportion, making it more suitable for the actual situation. Finally, the effectiveness of the method and model is verified based on the QGIS platform.

Citation Download Citation

Yan Cui, Kaifeng Zheng, and Pu Li "Research on grid data generation technology for field path planning of armored vehicles", Proc. SPIE 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 123460Q (27 September 2022); https://doi.org/10.1117/12.2654062

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KEYWORDS

Roads

Vegetation

Data modeling

Chemical elements

Geographic information systems

Multilayers

Algorithm development

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