Abstract
An efficient Preference based Evolutionary Qlearning algorithm (PEQL) for mobile robot path planning method is proposed that finds optimal path between source to destination using an improved policy evaluation with adaptive reward and policy switching process, the proposed mobile robot path planning algorithm is unique and novel since it finds the optimal path using policy switching and better success index than the conventional methods. Keywords: mobile robot, path planning, adaptive reward, policy switching
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.