Evaluation and Improvement of Global Pose Estimation with Multiple AprilTags for Industrial Manipulators

Abstract

Given the advancing importance for light-weight production materials an increase in automation is crucial. This paper presents a prototypical setup to obtain a precise pose estimation for an industrial manipulator in a realistic production environment. We show the achievable precision using only a standard fiducial marker system (AprilTag) and a state-of-the art camera attached to the robot. The results obtained in a typical working space of a robot cell of about 4.5m × 4.5m are in the range of 15mm to 35mm compared to ground truth provided by a laser tracker. We then show several methods of reducing this error by applying state-of-the-art optimization techniques, which reduce the error significantly to less than 10mm compared to the laser tracker ground truth data and at the same time remove existing outliers.