Abstract
Particle swarm optimization (PSO) algorithm is a new random global optimization algorithm, and the simple PSO algorithm (SPSOA) is short of high convergence speed, strong optimization ability and so on. To improve the optimization ability of SPSOA, the clonal copy, clonal crossover, hyper-mutation and clonal selection are introduced in the SPSOA, and a novel poly-clone particle swarm optimization algorithm (PCPSOA) is presented. Compared with the corresponding SPSOA and inertia weight PSO algorithm (IWPSOA), the simulation results of some complex functions optimization indicate that the proposed PCPSOA is characterized by strong searching ability and quick convergence speed. Finally, the PCPSOA is introduced into the path planning of mobile robot and the global path is optimized using PCPSOA on the basis of MAKLINK graph. The simulation results show that the path planning based on PCPSOA is feasible and effective.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
