Open Access
ARTICLE
3D Trajectory Planning of Positioning Error Correction Based on PSO-A* Algorithm
Huaixi Xing1, Yu Zhao1, Yuhui Zhang1, You Chen1, *
1 Air Force Engineering University, Xi’an, 710038, China.
* Corresponding Author: You Chen. Email: .
Computers, Materials & Continua 2020, 65(3), 2295-2308. https://doi.org/10.32604/cmc.2020.011858
Received 02 June 2020; Accepted 11 July 2020; Issue published 16 September 2020
Abstract
Aiming at the yaw problem caused by inertial navigation system errors
accumulation during the navigation of an intelligent aircraft, a three-dimensional trajectory
planning method based on the particle swarm optimization-A star (PSO-A*) algorithm is
designed. Firstly, an environment model for aircraft error correction is established, and the
trajectory is discretized to calculate the positioning error. Next, the positioning error is
corrected at many preset trajectory points. The shortest trajectory and the fewest correction
times are regarded as optimization goals to improve the heuristic function of A star (A*)
algorithm. Finally, the index weights are continuously optimized by the particle swarm
optimization algorithm. The optimal trajectory is found by the A* algorithm under the
current evaluation index, so the ideal trajectory is planned. The experimental results show
that the PSO-A* algorithm can quickly search for ideal trajectories in different environment
models, indicating that the algorithm has certain feasibility and adaptability, and verifies
the rationality of the proposed trajectory planning model. The PSO-A* algorithm has better
convergence accuracy than the A* algorithm, and the search efficiency is significantly
better than the grid search A star (GS-A*) algorithm. The PSO-A* algorithm proposed in
this paper has certain engineering application value. The researchers will study the realtime and systematic nature of the algorithm.
Keywords
Cite This Article
H. Xing, Y. Zhao, Y. Zhang and Y. Chen, "3d trajectory planning of positioning error correction based on pso-a* algorithm,"
Computers, Materials & Continua, vol. 65, no.3, pp. 2295–2308, 2020.
Citations