Outdoor Unmanned Vehicle System Design and Patrol Algorithm Research

In modern unmanned vehicle technology, outdoor patrolling algorithms play a crucial role in enabling autonomous navigation. To enhance the performance of unmanned vehicles in complex outdoor environments, researchers have been continuously refining and optimizing these algorithms. This paper presents a detailed overview of our approach, including the design of the autonomous navigation camera algorithm, vision processing, and recognition technologies. To address challenges such as limited computational resources, environmental interference in line patrolling, and the prolonged debugging time required for the line patrolling algorithm, we propose innovative solutions. These include multi-threading, segmented adaptive binarization, the edge inheritance method, the least squares approach, and enhancements to the YOLOv5-Lite model. Together, these advancements significantly improve the vehicle's adaptability to diverse lane conditions.