Overhead vision system for testing swarms and groups of wheeled robots

• Autorzy: Wiech Jakub , Hendzel Zenon

Identyfikatory

DOI

10.14313/JAMRIS/2-2019/14

• Języki publikacji: EN

Abstrakty

EN

The paper describes how to use ArUco markers to determine the position and orientation of wheeled robots in 3D space. it is preceded by a general description on the testbed and a detailed description on the marker detection algorithm along with the camera calibration using the ChaArUco markers. The camera has been described and calibrated using the pinhole camera model, taking into account distortion on the lens. The second part oo the article describes the wheeled robots with their mechanical construction.

Słowa kluczowe

EN

swarm robotics; vision system; wheeled robots

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2019
• Tom: Vol. 13, No. 2
• Strony: 15--22
• Opis fizyczny: Bibliogr. 14 poz., rys.

Twórcy

autor

Wiech Jakub

• Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics

autor

Hendzel Zenon

• Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics

Bibliografia

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• [11] P. C. Santos, A. Stork, A. Buaes, C. E. Pereira, and J. Jorge, “A real-time low-cost markerbased multiple camera tracking solution for virtual reality applications”, Journal of Real-Time Image Processing, vol. 5, no. 2, 2010, 121–128, 10.1007/s11554-009-0138-9.
• [12] J. S. Tutak and J. Wiech, “Horizontal Automated Storage and Retrieval System”, Advances in Science and Technology Research Journal, vol. 11, no. 1, 2017, 82–95, 10.12913/22998624/68470.
• [13] R. S. Xavier, B. M. F. d. Silva, and L. M. G. Gonzalves, “Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization”. In: 2017 Workshop of Computer Vision (WVC), 2017, 73–77, 10.1109/WVC.2017.00020.
• [14] Z. Zhang, “A flexible new technique for camera calibration”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 11, 2000, 1330–1334, 10.1109/34.888718.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).