Hierarchical-Optimization-Based Grinding Planning of Robotic Arms for Tubular Workpieces

Abstract

In order to accomplish the adaptive grinding tasks for tubular workpieces, a hierarchical-optimization-based grinding planning framework is proposed in this article. For various tubular workpieces of different sizes, spatial orientations, and surface characteristics, uniform grinding is accomplished by the proposed planning framework with the following three goals met simultaneously: 1) optimal grinding order; 2) maximum rate of convergence; and 3) minimum computational complexity. In the planning framework proposed, three calculation modules for geometric parameter estimation, hierarchical optimal sorting, and parameterized grinding control are contained; the optimization module and the grinding control module are based on hierarchical optimization mechanism and velocity-vector-decomposition-based (VVD-based) parameterized path generation method designed in this article, respectively. Compared with the state-of-the-art algorithms, the quantitative performance advantages of our grinding planning framework are validated by experimental results. Specifically, in terms of geometric parameter estimation, convergence rate, computational complexity, and uniform grinding effect, the performance advantages are at least 20.75%, 25.71%, 47.17%, and 18.87%, respectively.