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Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments
Frontiers of Information Technology & Electronic Engineering ( IF 1.033 ) Pub Date : 2020-05-21 , DOI: 10.1631/fitee.1900659
Yan Shao, Zhi-feng Zhao, Rong-peng Li, Yu-geng Zhou

Coordinating multiple unmanned aerial vehicles (multi-UAVs) is a challenging technique in highly dynamic and sophisticated environments. Based on digital pheromones as well as current mainstream unmanned system controlling algorithms, we propose a strategy for multi-UAVs to acquire targets with limited prior knowledge. In particular, we put forward a more reasonable and effective pheromone update mechanism, by improving digital pheromone fusion algorithms for different semantic pheromones and planning individuals’ probabilistic behavioral decision-making schemes. Also, inspired by the flocking model in nature, considering the limitations of some individuals in perception and communication, we design a navigation algorithm model on top of Olfati-Saber’s algorithm for flocking control, by further replacing the pheromone scalar to a vector. Simulation results show that the proposed algorithm can yield superior performance in terms of coverage, detection and revisit efficiency, and the capability of obstacle avoidance.
更新日期:2020-05-21

 

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