Abstract
This paper proposes an optimal path planning algorithm for mobile robots based on Particle Swam Optimization with an Aging Leader and Challengers (ALC-PSO) and Rapidly-exploring Random Tree (RRT), it improved algorithm of ALC-PSO to imitate concept of RRT root node grown into goal point in path planning, and add Danger Degree Map to avoid obstacles, this method is not only overcome the drawback for particle swam optimization which is easy to fall into local optimization in robotic path planning and the basic Rapidly-exploring Random Tree path planning in avoiding the premature convergence problem, but also improve both of algorithm which can't plan in dynamic environment. From the results of simulations, we show that this algorithm can improve the stability of RRT path planning in dynamic environment, and ensure that the path is almost optimal.
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.
