This paper presents a systematic approach for representing and estimating the Cartesian positioning errors of robot manipulators with analytical functions such as Fourier polynomials and ordinary polynomials. A Motoman SK 120 robot manipulator was employed as an experimental system to evaluate the efficacy of the approach. As a complementary part of this evaluation process, the kinematic parameters of the experimental system are also identified. The position data needed throughout this study were provided by a laser-based dynamic measurement system. The coefficients of the polynomials and the kinematic parameters are determined using the position data for a number of identification configurations. The proposed approximation and estimation approach is verified experimentally for three exemplary Cartesian space trajectories, which describe different configurations of the manipulator. The errors estimated through the polynomials are then corrected using a first-order approximation of the inverse kinematic model. The numerical and experimental results prove that the analytical functions are accurate enough to estimate manipulator position errors without needing further experimental data. The principal conclusion is that our approach of estimating position errors with some analytical functions is practical and generic, and most importantly it is effective enough to improve robot accuracy.
|Number of pages||28|
|Journal||Mechanism and Machine Theory|
|Publication status||Published - 1 Aug 2005|
- Error estimation and compensation
- Laser-based dynamic sensing
- Parameter estimation
- Robot calibration