Complex curved surface robot efficient high-precision teaching method

Abstract

The invention belongs to the technical field of robot intelligent machining, and particularly discloses a complex curved surface robot efficient high-precision teaching method. The method comprises the following steps that S1, a to-be-taught robot is subjected to free traction so that kinesthetic teaching of a curved surface track can be completed, and kinesthetic teaching data are collected; S2,a virtual fixture is built according to the collected teaching data, assistance is provided for teaching of the next curved surface track through the built virtual fixture so that teaching of multiplecurved surface tracks can be completed, and the kinesthetic teaching data are obtained; S3, an incomplete curved surface manifold is built according to the existing kinesthetic teaching data, a virtual fixture is obtained, and teaching of the multiple curved surface tracks is completed with assistance of the virtual fixture; and S4, the error of the curved surface manifold is calculated, whetherthe error of the curved surface manifold is within the range of the threshold value is judged, if yes, the process is finished, and if no, the process goes back to the step S3. The method has the advantages of being good in practicality, easy to apply, high teaching efficiency and precision, and the like.

Description

technical field [0001] The invention belongs to the technical field of robot intelligent processing, and more specifically relates to a high-efficiency and high-precision teaching method for complex curved surface robots. Background technique [0002] With the continuous improvement of the industrial level, robots are widely used in grinding and polishing of large complex curved surfaces such as wind turbine blades and high-speed rail body-in-white due to their low cost, good flexibility, and high efficiency. At present, for the robot processing of large and complex surfaces, it often relies on two methods: off-line robot programming and teaching pendant programming. [0003] Robot offline programming has high accuracy, but it relies heavily on existing models and has poor generalization ability. From the perspective of cost, it is only suitable for mass processing of parts. Then it becomes more and more difficult, even impossible to some extent. Robot teaching programming...

AI Technical Summary

Problems solved by technology

[0003] Robot offline programming has high accuracy, but it relies heavily on existing models and has poor generalization ability. From the perspective of cost, it is only suitable for mass processing of parts. Then it becomes more and more difficult, even to some extent impossible

Robot teaching programming does not rely on existing models, and can transfer human experience to deal with some complex parts that are difficult to handle offline programming, but its overall teaching efficiency is low, low precision, and poor generalization ability

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