Research on path tracking algorithm of green agricultural machinery for sustainable development

Abstract

Path tracking is crucial for a variety of uses. Such as manufacturing, bandwidth utilization, virtual worlds, and farming. Allowing path-tracking techniques in wise agriculture is essential for the eventual advancement of farming technology. Proposed algorithms in agriculture are generally aimed at enhancing the velocity vector effectiveness of agricultural machinery and agriculture production is improved. In this research conducted a standardized studies on the conventional farming equipment technique using the farm equipment framework and predicated on the relevant research of problem based modelling to analyze the farm equipment convergence rate in the farm procedure incident, conducted the control scheme, constructed the convergence rate in the farm structure working principle using artificial intelligence techniques. When parameter observing, the DQN method enables farm equipment to adjust to the surroundings quicker, which enhances model predictive effectiveness. It is significant in terms of developing better measures to encourage instantaneous tracking and regulate of farm equipment in order to achieve effective agricultural mechanization processes.