Detecting Driving Hazards Using Point Cloud Data from LiDAR and AI for Industrial Navigation Robot

In this undergraduate research project, we use LiDAR mapping for object detection and further combine AI and computer vision algorithms to enable robots to safely drive the vehicle in a given environment. AI and computer vision technologies allow the robot to identify lanes and intersections, enabling vehicle navigation, while LiDAR mapping quickly and accurately determines the depth between the vehicle and objects entering a specific area. This capability allows the robot to temporarily stop the vehicle, preventing collisions with objects. Through these technologies, our goal is to prevent collisions that may occur during driving, ensuring pedestrian safety and enabling safe robot-driven vehicle operation in crowded places. Simulation and test have been conducted to verify the proposed methods.