# Research on 2D Laser Automatic Navigation Control for Standardized Orchard  
[PERSON]  
1 College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China; [EMAIL_ADDRESS] (S.Z. ); [EMAIL_ADDRESS] (C.G. ); [EMAIL_ADDRESS] (Z.G. ); [EMAIL_ADDRESS] (A.S.); [EMAIL_ADDRESS] (Y.C.) [PERSON]  
1 College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China; [EMAIL_ADDRESS] (S.Z. ); [EMAIL_ADDRESS] (C.G. ); [EMAIL_ADDRESS] (Z.G. ); [EMAIL_ADDRESS] (A.S.); [EMAIL_ADDRESS] (Y.C.) [PERSON]  
1 College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China; [EMAIL_ADDRESS] (S.Z. ); [EMAIL_ADDRESS] (C.G. ); [EMAIL_ADDRESS] (Z.G. ); sugibrayadilet@nwafu. The automatic navigation technology designed by the project senses the surrounding environment through the navigation system, and then the system can assist the robot to complete different tasks. This experiment is an important part of the development of advanced agricultural machinery equipment [4; 5; 6]. In the early research, many scholars focused on the physical navigation system based on physical orbit [7] and ultrasonic sensor [8], but the systems are susceptible to external environment interference and the labor is not completely liberated. With the continuous development of environment-aware location technology, GNSS navigation has gradually become a research hot-spot [9; 10; 11]. It demonstrates superiority and great potential in empty environment. However, in the orchard environment, the canopy and branches of the fruit trees are dense, and the GNSS system cannot receive satellite signals stably due to the shadowing, so the applicability is poor. The difficulty of this experiment lies in the machine vision navigation technology, which is a comprehensive technology based on digital image processing, which has the advantages of great flexibility and rich information acquisition. At present, the types of visual sensors commonly used are mainly monocular cameras and binocular cameras. Monocular cameras are simple in structure and can be used for navigation path extraction in certain types of known environments [12; 13], but only two-dimensional information is available due to structural limitations. As early as 1995, [PERSON] [14] first proved the feasibility of binocular vision technology for unmanned ground vehicles. In recent years, binocular vision technology has also been widely used in agriculture [15; 16; 17]. However, machine vision hardware is complex in structure, expensive and requires high performance on the processor. At the same time, image information is easily lost due to environmental noise, which affects the accuracy of the guidance system. Compared with visual navigation, laser navigation has many advantages such as high range accuracy and strong anti-interference ability. Laser navigation technology, according to different structures, can be divided into 2D laser and 3D laser. The 3D laser realizes environmental mapping in three-dimensional space by multi-line mixing (combining 2D laser or monocular vision) [18; 19; 20] or solid-state rotation (adding pan tilt scanning device) [21; 22; 23; 24]. Two-dimensional lasers typically use only one set of laser sensors to scan on one line. [PERSON] of Hokkaido University and [PERSON] of Northwest A&F University [25; 26; 27] designed a 2D laser automatic navigation system suitable for orchard environment and verified the reliability of the system with a small horsepower tractor as an experimental platform. After research, it was found that the lateral error in navigation was 11 cm and the heading angle error was 1.5\({}^{\circ}\). [PERSON] [28] of Tsukuba University in Japan used 2D lasers and Kubota Kingwel tractors as an experimental platform. The researchers at the university designed an automatic curve navigation driving system for orchards. The experiment showed that the average deviation of path-tracking was 0.275 m. The standard deviation is 0.009 mm.