Research on Intelligent Tool Setting Method for Complex Working Conditions Based on Combined Visual/Tactile Control

Aiming at the problems of low tool setting efficiency and control accuracy in the existing intelligent tool setting methods, this paper proposes an intelligent tool setting method based on Vision/Haptic interaction control. The method quickly and initially locates to the initial position of the haptic tool setting through vision, and then uses the haptic tool setting to search for precise positioning at a slow speed, which improves the tool setting efficiency under the guarantee of tool setting accuracy. First of all, the blade vision fast positioning module is built, using canny algorithm for edge detection, for the problem that the image quality collected under different working conditions is different and the fixed voting parameters of the Hough transform method may cause the loss of contour features or misjudgment, the Hough plus clustering method is utilized to improve the robustness of the algorithm in identifying the contour, and to realize the fast positioning of the blade force sense to the origin of the blade; Secondly, based on the material parameters and geometric model to establish the end face grinding force model, instead of the actual sampling results, the rise time, adjustment time and maximum overshooting amount as the optimization objectives, combined with the particle swarm algorithm to optimize the parameters of the PID controller, which in turn improves the tactile tool setting control accuracy and efficiency; Finally, the tool setting algorithm is verified by building an experimental platform. The experimental results show that the method can realize accurate automatic tool setting quickly and stably, and the tool setting error can be controlled within 0.01mm.