Abstract
Particle Swarm Optimization (PSO) algorithm is a simple approach with premature convergence and stagnation prone. The loss of efficiency and sub-optimal solution occur frequently while solving path planning problem with PSO. Therefore, a method is proposed to optimize parameters which affect performance of the PSO algorithm by using Rauch–Tung–Striebel (RTS) smoother. Moreover the Metropolis Criterion is applied as acceptance policy, which can prevent the PSO algorithm from falling into local minimums in the proposed method. The RTS smoother is applied to eliminate the irregular error of the PSO updated position, and to smooth the produced path. Experimental results show the proposed method which is based on the fusion of the PSO, Metropolis Criterion and RTS performs better than the existing methods in terms of solution’s quality and robustness in the path planning problem for UAVs.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.