Path Planning of Multiple Unmanned Aerial Vehicles Covering Multiple Regions Based on Minimum Consumption Ratio

• Published in: Aerospace Vol. 10; no. 2; p. 93
• Main Authors: Chen, Jian, Zhang, Ruikang, Zhao, Hongqiang, Li, Jiejie, He, Jilin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2023
• Subjects: Algorithms; Collaboration; Drone aircraft; dynamic planning; Dynamic programming; Energy consumption; Farms; Genetic algorithms; Heuristic; Heuristic methods; Linear programming; minimum consumption ratio; Numerical experiments; Optimization; Parameters; path planning; Pesticides; Planning; region allocation; Regions; Sensors; Trajectory planning; Traveling salesman problem; UAV; Unmanned aerial vehicles; New York
• ISSN: 2226-4310; 2226-4310
• DOI: 10.3390/aerospace10020093

Investigating the path planning of multiple unmanned aerial vehicles (UAVs) covering multiple regions, this work proposes an effective heuristic method of region coverage path planning to reduce the complexity of the problem. The proposed method decomposes the solution process into two stages. First of all, the two most important parameters affecting the performance of UAV missions were considered, namely, the flying speed and the scan width. According to these two parameters of UAVs, a new multi-regional allocation scheme based on the minimum consumption ratio was proposed. With this allocation scheme, the coverage task allocation and path pre-planning of UAVs were obtained. Then, the UAVs’ trajectory routes were optimized based on the dynamic planning algorithm to reduce the time consumption of UAVs on the transfer path between regions. The method was evaluated with numerical experiments. The results showed that the proposed method can effectively solve the path planning problem of multiple UAVs covering multiple regions. Compared with an advanced algorithm, the time consumption for homogeneous and heterogenous UAV performance was reduced by 5.1% and 3%, respectively.