A Review of Navigation and SLAM Technologies in Orchard Environments

Abstract

This paper reviews the research status of orchard environment navigation technology and Simultaneous Localization and Mapping (SLAM) technology. In the field of orchard navigation, researchers primarily utilize LiDAR and visual sensors to achieve autonomous navigation, enhancing the operational efficiency of robots through map construction and path planning. LiDAR, with its all-weather operational capability, shows broad application prospects in orchard environments, while visual sensors perform poorly under limited lighting conditions. As a core technology for robot navigation, SLAM has evolved from traditional methods to modern optimization algorithms. Currently, laser SLAM and visual SLAM each have their advantages in different scenarios. Laser SLAM demonstrates higher robustness in complex environments, while visual SLAM is more cost-effective and better at capturing detailed environmental information. Future research will focus on multi-sensor fusion and algorithm optimization to further improve the navigation capabilities of robots in complex environments.