A lawn care robot based on the BAS-optimised fuzzy PID control strategy and the GC-YOLOv8 target detection algorithm

With the increasing public demand for environmentally friendly technologies and automated equipment, it has become increasingly important to develop efficient and environmentally friendly lawn care solutions. In this paper, a weeding system based on BAS optimised fuzzy PID control strategy is proposed with the aim of improving weeding efficiency and accuracy. The system incorporates the GC-YOLOv8s target detection model to accurately identify and effectively avoid pedestrians and other obstacles during the weeding process. Meanwhile, an edge recognition algorithm is used to enhance the robot's sensitivity to edge features, thus improving recognition accuracy. The experimental results show that compared with the traditional algorithm, the BAS optimised fuzzy PID control strategy significantly reduces the amount of overshooting of the system and accelerates the response time; while the GC-YOLOv8s-based target recognition system shows excellent performance under different lighting and environmental conditions, and is able to process images in real time and respond quickly.