Abstract
In this article, the problem of real-time robot exploration and map building (active SLAM) is considered. A single stereo vision camera is exploited by a fully autonomous robot to navigate, localize itself, define its surroundings, and avoid any possible obstacle in the aim of maximizing the mapped region following the optimal route. A modified version of the so-called cognitive-based adaptive optimization algorithm is introduced for the robot to successfully complete its tasks in real time and avoid any local minima entrapment. The method’s effectiveness and performance were tested under various simulation environments as well as real unknown areas with the use of properly equipped robots.
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.
