A Novel Parameter Optimization Method for the Driving System of High-Speed Parallel Robots

Abstract

Driving system parameters optimization, especially the optimal selection of specifications of motor and gearbox, is very important for improving high-speed parallel robots' performance. A very challenging issue is parallel robots' performance evaluation that should be able to illustrate robots' performance accurately and guide driving system parameters optimization effectively. However, this issue is complicated by parallel robots' anisotropic translational and rotational dynamic performance, and the multiparameters of motors and gearboxes. In this paper, by separating the influence of translational and rotational degrees-of-freedom (DOFs) on robots' performance, a new dynamic performance index is proposed to reflect the driving torque in instantaneous acceleration. Then, the influence of driving system's multiparameters on robots' driving torque in instantaneous acceleration and cycle time in continuous motion is investigated. Based on the investigation, an inertia matching index is further derived which is more suitable for minimizing the driving torque of parallel robots with translational and rotational DOFs. A comprehensive parameterized performance atlas is finally established. Based on this atlas, the performance of a high-speed parallel robot developed in this paper can be clearly evaluated, and the optimal combination of motors and gearboxes can be quickly selected to ensure low driving torque and high pick-and-place frequency.