Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments

作     者：Yan SHAO Zhi-feng ZHAO Rong-peng LI Yu-geng ZHOU Yan SHAO;Zhi-feng ZHAO;Rong-peng LI;Yu-geng ZHOU

作者机构：College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou 310027China Zhejiang LabHangzhou 311121China Institute of Wanfeng Jinyuan Holding Group Co.Ltd.Shaoxing 312000China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2020年第21卷第5期

页      面：796-808页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081104[工学-模式识别与智能系统] 0839[工学-网络空间安全] 082503[工学-航空宇航制造工程] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Project supported by the National Key R&D Program of China(No.2017YFB1301003) the National Natural Science Foundation of China(Nos.61701439 and 61731002) the Zhejiang Key Research and Development Plan(Nos.2019C01002and 2019C03131) the Pro ject sponsored by Zhejiang Lab(No.2019LC0AB01) the Zhejiang Provincial Natural Science Foundation of China(No.LY20F010016)。 

主　　题：Collective intelligence Digital pheromones Artificial potential field Navigation algorithm 

摘      要：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.