SLAM-based turning strategy in restricted environments for car-like mobile robots

In the present work, a strategy to turn a car-like mobile robot in a restricted environment is presented. The strategy uses a Simultaneous Localization and Map Building (SLAM) algorithm to localize the robot in the environment and uses the map generated by the SLAM in the reverse movement of the turning strategy. The planning strategy takes into account the variance propagation in the predicted path for ensure the safe driving of the robot. In all the cases, the robot is considered as a body in movement, not as a point, to exploit all the navigable space. The vehicle is commanded by a kinematic trajectory controller. Real time experimental results are also shown in this work.