Robot mobile navigation is a hard task that requires, essentially, avoiding static and dynamic objects. This chapter presents a strategy for constructing an occupancy map by proposing a probabilistic model of an ultrasonic sensor, during robot indoor navigation. A local map is initially constructed using the ultrasonic sensor mounted in the front of the robot. This map provides the position of the nearest obstacles in the scene useful for achieving the reactive navigation. The encoders allow computing the robot location in the initial local map. A first path for robot navigation based on the initial local map is estimated using the potential field strategy. As soon as the robot starts its trajectory in real indoor environments with obstacles, the sensor continuously detects and updates the occupancy map by the logsig strategy. A Gaussian function is used for modelling the ultrasonic sensor with the aim of reaching higher precision of the distance measured for each obstacle in the scene. Experiments on detecting, mapping and avoiding obstacles are performed using the mobile robotic platform DaNI 2.0 and the VxWorks system. The resulted occupancy grid is analysed and discussed at the end of this document.
Part of the book: Robot Control