Implementation of LIDAR for Navigation, Geometric Shape Mapping, and Center of Mass

This study examines the capability of LIDAR (Light Detection and Ranging) to enhance autonomous vehicle navigation through laser-based distance measurement. LIDAR technology, which has become increasingly vital in robotics and autonomous vehicles, enables real-time object identification and mapping with high accuracy. The integration of LIDAR with the Robot Operating System (ROS) further enhances the system's capabilities by providing a robust framework for sensor data processing and control algorithms in autonomous system. In this research, LIDAR is applied to indoor navigation, focusing on mapping objects in the shapes of rectangles, triangles, and circles. The data obtained from LIDAR is used by a condition-based (if-else) navigation system on a mobile robot to determine the dimensions of objects and the location of their center points. The results show that LIDAR can provide effective feedback in navigation systems, with object mapping consistent with pre-configured maps. The mapping error rate recorded is 1.93%, demonstrating that this technology is reliable for autonomous navigation applications.