Mechanical and Electronic Engineering Design and Control Technology under Artificial Intelligence

With the continuous improvement of industrial processing automation, artificial fruit picking can no longer meet the requirements of today's processing efficiency. Therefore, automatic fruit picking robots are increasingly integrated into mechanized production, making the study of robot motion space very important. At present, there is a lot of research in the academic community. The traditional method for designing robot motion trajectories is usually optimized in terms of motion time and travel speed, rather than in terms of motion space. In order to further optimize the braking force distribution model of the electromechanical braking system, this paper takes the melon and fruit picking machinery equipment model as an example, fully considers the factors of idle frequency and full load, and conducts performance optimization analysis of the electromechanical braking system based on the PSO (Particle Swarm Optimization) algorithm. This article takes the ideal braking force distribution curve as the starting point, determines the objective function and constraint function, and selects the PSO algorithm to search for constraint inequality problems. Finally, the experimental results showed that the damage rate of the PSO algorithm was below 0.5% for different fruit picking quantities, while the ACO (Ant Colony Optimization) algorithm had the smallest damage rate of 0.9% and the highest damage rate of 2.3%.