Frontiers of Information Technology & Electronic Engineering
>> 2020,
Volume 21,
Issue 5
doi:
10.1631/FITEE.1900659
Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments
Affiliation(s): College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China; Zhejiang Lab, Hangzhou 311121, China; Institute of Wanfeng Jinyuan Holding Group Co., Ltd., Shaoxing 312000, China; less
Received: 2019-11-30
Accepted: 2020-05-18
Available online: 2020-05-18
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Abstract
Coordinating multiple unmanned aerial vehicles (multi-UAVs) is a challenging technique in highly dynamic and sophisticated environments. Based on 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 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.
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