UAV path planning using artificial potential field method updated by optimal control theory

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constr...

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Bibliographic Details
Published in:International journal of systems science 2016-04, Vol.47 (6), p.1407-1420
Main Authors: Chen, Yong-bo, Luo, Guan-chen, Mei, Yue-song, Yu, Jian-qiao, Su, Xiao-long
Format: Article
Language:English
Subjects:
additional control force
artificial potential field (APF)
Computer simulation
Constraints
functional optimisation problem
Mathematical models
Optimal control
Optimization
Path planning
Potential fields
Unmanned aerial vehicles
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Summary:The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.
ISSN:0020-7721
1464-5319
DOI:10.1080/00207721.2014.929191