[1]WANG Wenbin,QIN Xiaolin,ZHANG Lige,et al.Dynamic UAV trajectory planning based on receding horizon[J].CAAI Transactions on Intelligent Systems,2018,13(4):524-533.[doi:10.11992/tis.201708031]
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Dynamic UAV trajectory planning based on receding horizon

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 4 Page number: 524-533 Column: 学术论文—智能系统 Public date: 2018-07-05
Title:
Dynamic UAV trajectory planning based on receding horizon
Author(s):
WANG Wenbin1; 2;  QIN Xiaolin1; 2; 3;  ZHANG Lige1; 2;  ZHANG Guohua1; 2
1. Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, China;
2. School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100080, China;
3. Academy of Intelligent Software, Guangzhou University, Guangzhou 510006, China
Keywords:
trajectory planning; receding horizon control; VORONOI graph; variable weight; particle swarm optimization; artificial potential field
CLC:
TP18;V279
DOI:
10.11992/tis.201708031
Abstract:
Using receding horizon control and fast particle swarm optimization (RHC-FPSO), in this paper, we propose an algorithm for unmanned aerial vehicle (UAV) trajectory planning with dynamic constraints. We introduce the cost map method based on the VORONOI graph to estimate the distance from the end point of the trajectory to the target point. Using the concept of receding horizon control and the artificial potential field method, the path planning problem is transformed into an optimization problem, with the minimum distance and other performance indicators as cost functions. We design the evaluation function criteria based on the evaluation criteria and obtain the solution using a particle swarm optimization algorithm with variable weight. To address the problem in which a UAV approaches a danger zone, we introduce a repulsion field into the cost function to ensure safety. The simulation results show that the proposed method can effectively avoid obstacles within the constraint conditions and perform dynamic calculations in a complicated environment.
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