Improved Pose Estimation of Aruco Tags Using a Novel 3D Placement Strategy

Petr Oščádal; Dominik Heczko; Aleš Vysocký; Jakub Mlotek; Petr Novák; Ivan Virgala; Marek Sukop; Zdenko Bobovský

doi:10.3390/s20174825

Improved Pose Estimation of Aruco Tags Using a Novel 3D Placement Strategy

Sensors (Basel). 2020 Aug 26;20(17):4825. doi: 10.3390/s20174825.

Authors

Petr Oščádal¹, Dominik Heczko¹, Aleš Vysocký¹, Jakub Mlotek¹, Petr Novák¹, Ivan Virgala², Marek Sukop³, Zdenko Bobovský¹

Affiliations

¹ Department of Robotics, Faculty of Mechanical Engineering, VSB-TU Ostrava, 70833 Ostrava, Czech Republic.
² Department of Mechatronics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, Slovakia.
³ Department of Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, Slovakia.

Abstract

This paper extends the topic of monocular pose estimation of an object using Aruco tags imaged by RGB cameras. The accuracy of the Open CV Camera calibration and Aruco pose estimation pipelines is tested in detail by performing standardized tests with multiple Intel Realsense D435 Cameras. Analyzing the results led to a way to significantly improve the performance of Aruco tag localization which involved designing a 3D Aruco board, which is a set of Aruco tags placed at an angle to each other, and developing a library to combine the pose data from the individual tags for both higher accuracy and stability.

Keywords: 3D grid board; Aruco; pose estimation; precision.

Publication types

Letter

Abstract

Publication types

Grants and funding