A New Workspace and Structural Parameter Optimization Method of Parallel Robot

The parallel robot workspace refers to the set of points and boundary that can be reached by the parallel mechanism. With the continuous development and industrial application of parallel robots, the workspace analysis and optimization becomes a critical link in this process. In this paper, a workspace solution approach based on seed space segmentation and principal component analysis is proposed. In order to improve the working performance of parallel robots, a flexible workspace evaluation method based on quadratic fourth moment is proposed, and a relationship model between flexible workspace and structural parameters is established. Furthermore, based on the multi-objective genetic algorithm, the structure parameters of the parallel robot are optimized by the workspace and flexible workspace indexes. Finally, the advantage and effectiveness of proposed method are verified by experiment and comparison with traditional methods.