An advanced sonar morphology-based posterior approach (SMP) to building an occupancy grid map for a mobile robot is proposed in this study. It is very important for a mobile robot to find its surrounding saliencies and to localize itself for indoor navigation. Ultrasonic sensors are of great practical value in building environmental maps and for autonomous operation. However, grid maps constructed by ultrasonic sensors cannot typically form a realistic representation of a given environment due to incorrect sonar measurements caused by specular reflection and wide beam width. The sonar sensor model proposed in this study, in which the negative effect of incorrect sonar measurements is minimized by geometric association with sonar footprints, is adopted to build a high-quality grid map. Experimental results and evaluations in home and corridor environments demonstrate the validity of the proposed methods.

A new systematic exploration method is addressed that permits a mobile robot to effectively acquire the information on an unknown environment without wasting time. The algorithm is composed of following three modules: the first is the decomposition of a workspace into several sub-nodes by employing the concept of Quadtree. These nodes are chosen as sub-goals to be reached successively. The second is that controls the robot to follow the boundaries of objects in the environment in order to reach each sub-goal avoiding the situation of the robot entering a local minima. Here we utilize the imaginary distance forces exerted by objects. The third is the node conditions for estimating the map quality for each node, which enables the robot to remove sufficiently informed nodes from the Quadtree. Two conditions are defined for the estimation of the map quality; entropy and maximum level of Quadtree. The proposed approaches were successfully implemented to our mobile robot equipped with sonar sensors for constructing a sonar map of an unknown environment in a real world.