Faucet milling robot arm path planning based on ant colony algorithm

In order to improve the machining quality and efficiency of the robot for faucet milling, a robot milling path planning method with the shortest path is proposed. Using the UR10e robot as a model, the working principle of the robot is analyzed, and at the same time, the motion simulation model of the robot is established. Then, for the robot milled faucet, laser 3D scanning is used to accurately obtain its point cloud map, and the improved CC section method is used to obtain 1.75% robot milling paths. The processing path points are simplified according to the curvature sampling method under the premise of ensuring the milling profile. Then combined with the genetic algorithm continuous evolutionary iteration, the optimal solution of the shortest milling path is searched. Through simulation and actual test, the genetic algorithm has about 1% positive optimization effect on the path in terms of optimal trajectory optimization. The trajectory is optimized for some non-critical parts to improve the efficiency and accuracy of water dragon milling processing, which proves that the method is feasible.