Abstract
The basic ant colony algorithm for mobile robot path planning exists many problems, such as lack of stability, algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes improvement measures. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm. Simulation results show that the improved optimal path length significantly less than the basic ant colony algorithm and volatility is smaller, stability significantly improves. The stability of improved ant colony algorithm is superior to the basic ant colony algorithm, verify the effectiveness of the improvement measures.
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.
