Analysis of robot drive train errors, their static effects, and their compensations

Abstract

A mathematical model of the kinematic nonlinear drive-train errors, which reduce the absolute static positioning accuracy of robot arms, is presented. This kinematic inaccuracy renders robot manipulators less effective when programmed offline, though they might be programmed to successfully perform the same task by teach playback schemes. The kinematic drive-train inaccuracy model presented can be used to predict and compensate for these nonlinear effects online, without resorting to sensor-based programming techniques, which are often expensive and may be difficult to implement in an industrial environment. The drive-train error model presented is based on gear backlash, eccentricity, and drive-shaft compliance. That the effects of these nonlinearities severely impact the robot's repeatability and absolute positioning accuracy is mathematically proven. >