In recent years, the rapid development of big data, the Internet, and artificial intelligence has significantly advanced agriculture. The integration of information technology has bolstered agricultural modernization, enhancing management efficiency and reducing labor intensity. In the era of agricultural informatization, achieving automation and intelligence in agricultural machinery is crucial for improving production competitiveness and realizing modernization. Therefore, agricultural machinery researchers must carefully consider the future directions of automation and intelligence in their field.
I. Application of Agricultural Machinery Technology in Agricultural Informatization
1. Environmental Perception in Autonomous Driving
Machine vision technology extracts information in the form of images, integrates and analyzes it, and is used to capture environmental conditions. It can locate targets, plan paths, and control driving during autonomous driving, ensuring that agricultural machinery avoids obstacles and operates safely by recognizing targets through image acquisition and analysis.
2. Recognition and Positioning of Operational Targets
Agricultural robots utilize machine vision technology to identify and locate specific work targets. Tailored to various agricultural tasks, such as fruit picking and weeding, machine vision determines factors like fruit maturity and weed presence. This capability enables precise application of chemicals and efficient task execution.
3. Path Planning and Tracking Control
Path planning addresses issues of autonomous navigation in agricultural machinery. This technology improves the efficiency and quality of agricultural machinery work and reduces labor costs. Through path planning and tracking control, agricultural robots can autonomously travel along preset routes. Common control methods include PID control, fuzzy adaptive control, and neural networks, which ensure that agricultural machinery can continuously operate along the predetermined trajectory.
