The registration system for the evaluation of indoor visual slam and odometry algorithms

• Autorzy: Schmidt A. , Kraft M. , Fularz M. , Domagała Z.
• Języki publikacji: EN

Abstrakty

EN

This paper presents the new benchmark data registra- tion system aimed at facilitating the development and evaluation of the visual odometry and SLAM algorithms. The WiFiBOT LAB V3 wheeled robot equipped with three cameras, XSENS MTi atitude and heading reference system (AHRS) and Hall encoders can be used to gather data in indoor exploration scenarios. The ground truth trajectory of the robot is obtained using the visual motion tracking system. Additional static cameras simulating the surveillance network, as well as artificial markers augmen ting the navigation are incorporated in the system. The datasets registered with the presented system will be freely available for research purposes.

Słowa kluczowe

EN

SLAM; visual odometry; benchmark

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2013
• Tom: Vol. 7, No. 2
• Strony: 46--51
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Schmidt A.

• Poznań University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3A, 60-965 Poznań, Poland

autor

Kraft M.

• Poznań University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3A, 60-965 Poznań, Poland

autor

Fularz M.

• Poznań University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3A, 60-965 Poznań, Poland

autor

Domagała Z.

• Poznań University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3A, 60-965 Poznań, Poland

Bibliografia

• [1] D. Scaramuzza, F. Fraundorfer, ,,Visual Odometry: Part I - The First 30 Years and Fundamentals", IEEE Robotics and Automation Magazine, vol. 18(4), 2011, pp. 80-92.
• [2] F. Fraundorfer, D. Scaramuzza, ,,Visual Odometry: Part II - Matching, Robustness and Applications", IEEE Robotics and Automation Magazine, vol. 19(2), 2012, pp. 78-90.
• [3] A. J. Davison, I. Reid, N. Molton, O. Stasse, ,,MonoSLAM: Real-Time Single Camera SLAM", IEEE Trans. PAMI, vol. 29(6), 2007, pp. 1052-1067.
• [4] A. Schmidt, A. Kasińsksi, ,,The Visual SLAM System for a Hexapod Robot", Lecture Notes in Computer Science, vol. 6375, 2010, pp. 260-267.
• [5] S. Ceriani, G. Fontana, A. Giusti, D. Marzorati, M. Matteucci, D. Migliore, D. Rizzi, D. G. Sorrenti, P. Taddei, ,,RAWSEEDS ground truth collection systems for indoor self-localization and mapping", Autonomous Robots Journal, vol. 27(4), 2009, pp. 353-371.
• [6] S. M. Abdallah, D. C. Asmar, J. S. Zelek, ,,Towards benchmarks for vision SLAM algorithms", In: Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006, pp. 1542-1547.
• [7] J. Sturm, N. Engelhard, F. Endres, W. Burgard, D. Cremer, ,,Towards a benchmark for RGB-D SLAM evaluation", In: Proc. of the RGB-D Workshop on Advanced Reasoning with Depth Cameras at Robotics: Science and Systems Conf. (RSS), 2011.
• [8] J. Funke, T. Pietzsch, ,,A Framework for Evaluating Visual SLAM", In: Proc. British Machine Vision Conference, 2009.
• [9] http://www.wifibot.com
• [10] R. M. Haralick, Ch.-N. Lee, K. Ottenberg, M. Noelle, ,,Review and analysis of solutions of the three point perspective pose estimation problem", International Journal of Computer Vision, vol. 13(3), 1994, pp. 331-356.
• [11] http://opencv.org
• [12] R. Baczyk, ,,Wizyjny system nawigacyjny oparty na zmodyfikowanej metodzie samolokalizacji i tworzenia modelu otoczenia robota", PhD Thesis, Poznan University of Technology, 2007.
• [13] K. Lee, J. Eidson, ,,IEEE-1588 Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems", In: 34th Annual Precise Time and Time Interval (PTTI) Meeting, 2002, pp. 98-105.