Journal
ACTUATORS
Volume 11, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/act11010004
Keywords
multiple UAVs; mission assignment; path planning; genetic algorithm; artificial bee colony; disaster rescue
Funding
- Fund of Science and Technology on Near-Surface Detection Laboratory [TCGZ2019A003]
- National Natural Science Foundation of China [61975011]
- Fund of State Key Laboratory of Intense Pulsed Radiation Simulation and Effect [SKLIPR2024]
- Fundamental Research Fund for the China Central Universities of USTB [FRF-BD-19-002A]
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An optimal mission assignment and path planning method for multiple UAVs in disaster rescue is proposed. The method considers various threat sources and cost-revenue function, and utilizes AGA and IABC algorithms for mission assignment and path planning. Extensive simulation experiments demonstrate the effectiveness of the proposed method.
An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include the drug delivery UAV, image collection UAV, and communication relay UAV. When implementing the modeling and simulation, first, three threat sources are built: the weather threat source, transmission tower threat source, and upland threat source. Second, a cost-revenue function is constructed. The flight distance, oil consumption, function descriptions of UAV, and threat source factors above are considered. The analytic hierarchy process (AHP) method is utilized to estimate the weights of cost-revenue function. Third, an adaptive genetic algorithm (AGA) is designed to solve the mission allocation task. A fitness function which considers the current and maximum iteration numbers is proposed to improve the AGA convergence performance. Finally, an optimal path plan between the neighboring mission points is computed by an improved artificial bee colony (IABC) method. A balanced searching strategy is developed to modify the IABC computational effect. Extensive simulation experiments have shown the effectiveness of our method.
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