Computer Vision Based Recognition Algorithm for Sea Buckthorn Harvesting Robot

Sea buckthorn harvesting presents challenges in labour requirements and costs, urging the need for technological advancements. This paper discusses the applicability of adaptive systems, computer vision, and robotics in agricultural tasks, focusing on the development of an autonomous computer vision-based sea buckthorn harvesting robot. The paper outlines the overall architecture of the robot and presents results demonstrating its detecting ability. Additionally, a branch direction detection algorithm is described. The research shows satisfactory precision levels for detection on known samples, although precision for new samples requires improvement in future research steps. The outlined conclusions highlight the achieved milestones in the development of the sea buckthorn harvesting robot and emphasize areas for further refinement and enhancement.