A novel robot calibration method with plane constraint based on dial indicator

TL;DR

This paper introduces a cost-effective robot calibration method using plane constraints and a dial indicator, employing advanced filtering and optimization algorithms to improve accuracy amidst measurement noise.

Contribution

The paper presents a novel calibration approach combining plane constraints, SCKF filtering, and LM optimization, reducing costs and enhancing accuracy compared to traditional methods.

Findings

Effective calibration accuracy achieved in experiments

Cost reduction through dial indicator usage

Robustness against measurement noise demonstrated

Abstract

In pace with the electronic technology development and the production technology improvement, industrial robot Give Scope to the Advantage in social services and industrial production. However, due to long-term mechanical wear and structural deformation, the absolute positioning accuracy is low, which greatly hinders the development of manufacturing industry. Calibrating the kinematic parameters of the robot is an effective way to address it. However, the main measuring equipment such as laser trackers and coordinate measuring machines are expensive and need special personnel to operate. Additionally, in the measurement process, due to the influence of many environmental factors, measurement noises are generated, which will affect the calibration accuracy of the robot. Basing on these, we have done the following work: a) developing a robot calibration method based on plane constraint to simplify measurement steps; b) employing Square-root Culture Kalman Filter (SCKF) algorithm for reducing the influence of measurement noises; c) proposing a novel algorithm for identifying kinematic parameters based on SCKF algorithm and Levenberg Marquardt (LM) algorithm to achieve the high calibration accuracy; d) adopting the dial indicator as the measuring equipment for slashing costs. The enough experiments verify the effectiveness of the proposed calibration algorithm and experimental platform.