Using D* algorithm to optimize the path selection of UAV in different environments

Jiazhe Wang; Zhiqi Wang; Xiaofei Yang

doi:10.1117/12.3027181

1 April 2024 Using D* algorithm to optimize the path selection of UAV in different environments

Jiazhe Wang, Zhiqi Wang, Xiaofei Yang

Proceedings Volume 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024); 130770O (2024) https://doi.org/10.1117/12.3027181
Event: 4th International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 2024, Chicago, IL, United States

Abstract

With the development of drones, UAVs are widely used in many fields such as military, life, agriculture, and commerce, among which low-altitude UAVs are the most widely used. Due to the complexity of the low-altitude environment, the requirements for the flight capability of the drone have also increased. In different working scenarios, factors such as wind speed, temperature, and humidity will affect the route of the drone, resulting in increased energy loss and reduced safety of the drone, and it may not be able to complete the task. To address this issue, a path planning method for UAV based on an improved D* algorithm is proposed. On the basis of the high matching between the D* algorithm and the dynamic environment, the cost function of the D* algorithm is dynamically adjusted according to the environmental factors, the heuristic estimation function algorithm is improved, and the correlation weight can be adjusted in real time according to the environment, and the path selection is adjusted and optimized to better cope with the changing environment. Simulation of MATLAB results show that the algorithm can reduce energy loss and enhance the adaptability of UAV to changing environments during operation, and has good adaptability in different environments.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiazhe Wang, Zhiqi Wang, and Xiaofei Yang "Using D* algorithm to optimize the path selection of UAV in different environments", Proc. SPIE 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 130770O (1 April 2024); https://doi.org/10.1117/12.3027181

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KEYWORDS

Wind speed

Unmanned aerial vehicles

Buildings

Mathematical optimization

Detection and tracking algorithms

Computer simulations

Safety

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