This thesis presents the development of a sensor fusion framework that integrates ultrasonic sensors with a rotating Light Detection and Ranging (LiDAR) system to generate an occupancy grid map. The objective is to improve spatial awareness for autonomous navigation by employing an adaptive LiDAR approach, wherein ultrasonic sensors are used to identify regions of interest for focused scanning.

The design and implementation of a test system are described, along with the development of an occupancy grid map capable of representing data from both LiDAR and ultrasonic sensors. To enhance the accuracy and reliability of the environmental representation, the occupancy grid map incorporates an inverse sensor model in combination with Bayesian statistical methods.