Agricultural Vehicle Automatic Navigation Positioning and Obstacle Avoidance Technology Based on ICP

Abstract

The problem of closed branches and leaves in orchards can cause satellite navigation systems to experience star loss, leading to safety issues such as collisions and loss of control. To address this issue, this study develops a multi-mode navigation control system for satellite navigation and sensor tracking, aiming to achieve multi-mode intelligent path judgment and ensure the accuracy and safety of operations. This method utilizes point cloud iterative nearest point algorithm LiDAR technology to gain 3D information of the surrounding environment when satellite signals are unavailable. Through perception and analysis of the environment, real-time path planning and obstacle avoidance decision-making are achieved. At the same time, through micro-inertial navigation technology, accurate perception and control of the position and attitude of navigation equipment are achieved, thereby achieving precise control of the operation process. According to relevant experimental data, the experimental distance accuracy based on the vehicle mounted daytime environment dataset was 84.88%, and the duration accuracy was 97.63%. Accordingly, the proposed system is capable of accurately determining the current position and heading, as well as making path planning and obstacle avoidance decisions based on real-time environmental information. This ensures the accuracy and safety of operations. The research method exhibits higher stability and reliability in orchard operations, providing an effective solution for the accuracy and safety of orchard operations.

Keywords

• Point cloud iteration nearest point algorithm
• agricultural vehicles
• automatic navigation and positioning
• obstacle avoidance technology
• scale invariant feature transformation