Real-Time Active SLAM and Obstacle Avoidance for an Autonomous Robot Based on Stereo Vision

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.