An intelligent control method for the spraying amount of a self-propelled weeder based on a dynamic programming algorithm

Abstract

When the self-propelled weeder reaches an obstacle, the amount of pesticide spraying does not change according to the actual situation, leading to an application imbalance. Therefore, an intelligent control method of spraying output of a self-propelled weeder based on a dynamic programming algorithm (DPA) was proposed. The dynamic norm algorithm transformed obstacle avoidance path planning into a multi-stage decision-making problem. The obstacle avoidance path was planned, and the pesticide dosage control equation was designed by using the PID control algorithm to realize the obstacle avoidance and variable application of self-walking weed killer. The experimental results show that the designed self-walking weeder can effectively avoid obstacles, and the maximum average dosage error is 1.4%. Therefore, the method can effectively apply the dosage according to the actual situation and guarantee the balance of spraying quantity.