To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).
First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.
Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.
The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.
This work was partially supported by the National Natural Science Foundation of China (Grant No. 61873125, 62073163), Support for projects in special zones for national defense science and technology innovation (2016300TS00911201), advanced research project of the equipment development (30102080101), National Defense Basic Research Program (JCKY2020605C009), Foundation Research Project of Jiangsu Province (The Natural Science Fund of Jiangsu Province, Grant No. BK20181291), the Aeronautic Science Foundation of China (Grant No. ASFC‐2020Z071052001), the Fundamental Research Funds for the Central Universities (Grant No. NZ2020004), Foundation of Key Laboratory of Navigation, Guidance and Health‐Management Technologies of Advanced Aerocraft (Nanjing Univ. of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Jiangsu Key Laboratory “Internet of Things and Control Technologies” & the Priority Academic Program Development of Jiangsu Higher Education Institutions, Science and Technology on Avionics Integration Laboratory, Supported by the 111 Project (B20007), Supported by Shanghai Aerospace Science and Technology Innovation Fund (SAST2019‐085), Introduction plan of high end experts (G20200010142).
Chao, L., Xiong, Z., Liu, J., Yang, C. and Chen, Y. (2021), "A brain-inspired localization system for the UAV based on navigation cells", Aircraft Engineering and Aerospace Technology, Vol. 93 No. 7, pp. 1221-1228. https://doi.org/10.1108/AEAT-09-2020-0194
Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited