The Artificial Intelligence Driven Autonomous Navigation Operation Path Planning System for Agricultural Machinery

Abstract

This study aims to develop an artificial intelligence-based autonomous navigation job path planning system for agricultural machinery. The core algorithm of the system combines path planning, monocular vision, visual navigation map, area detection and color calibration, etc., to realize autonomous navigation and efficient operation of agricultural machinery in complex farmland environments. The system uses the visual navigation map and area detection algorithm to identify and plan the path of the target area. The color calibration module further improves the accuracy of image information and provides higher reliability for path planning. The simulation results show that the system can accurately detect the working area in the complex farmland environment, plan the optimal path, and ensure the stability and efficiency of the mechanical operation. Accurate data analysis shows that the path planning success rate of the system is more than 90% in various farmland scenarios, effectively improving the automation level of agricultural machinery operations. This study provides a new idea and practical basis for future intelligent development of agricultural machinery.