UAV Path Planning Method Based on Epicauta Hirticornis Algorithm
Mengzhuo Zhang, San Li, Feng Qin, Chengquan An, Hongyuan Gao · 2024
To address the challenges encountered by UAVs in terrain environments fraught with multiple threats, a novel approach has been devised to not only evade these threats but also minimize overall costs. Named the Epicauta Hirticornis Algorithm (EHA),this method draws inspiration from the defensive mechanism of the Epicauta Hirticornis group, which secretes cantharidin as a warning to deter predators. By incorporating a grading system, EHA effectively identifies and circumvents threats. Extensive simulation experiments have been conducted to validate the effectiveness of the path planning scheme powered by EHA. These rigorous tests demonstrate that EHA not only excels at recognizing and evading threats but also crafts an optimal path that achieves a delicate balance between minimizing comprehensive costs and attaining the shortest possible route length. As a result, EHA outperforms other contemporary path planning techniques, offering a solution for UAVs navigating complex and hazardous terrain environments.