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Reliable Real-Time Ball Tracking for Robot Table Tennis

Gomez-Gonzalez, Sebastian ; Nemmour, Yassine ; Schölkopf, Bernhard ; Peters, Jan (2022):
Reliable Real-Time Ball Tracking for Robot Table Tennis. (Publisher's Version)
In: Robotics, 8 (4), MDPI, e-ISSN 2218-6581,
DOI: 10.26083/tuprints-00015740,

Available under: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Origin: Secondary publication DeepGreen
Status: Publisher's Version
Title: Reliable Real-Time Ball Tracking for Robot Table Tennis
Language: English

Robot table tennis systems require a vision system that can track the ball position with low latency and high sampling rate. Altering the ball to simplify the tracking using, for instance, infrared coating changes the physics of the ball trajectory. As a result, table tennis systems use custom tracking systems to track the ball based on heuristic algorithms respecting the real-time constrains applied to RGB images captured with a set of cameras. However, these heuristic algorithms often report erroneous ball positions, and the table tennis policies typically need to incorporate additional heuristics to detect and possibly correct outliers. In this paper, we propose a vision system for object detection and tracking that focuses on reliability while providing real-time performance. Our assumption is that by using multiple cameras, we can find and discard the errors obtained in the object detection phase by checking for consistency with the positions reported by other cameras. We provide an open source implementation of the proposed tracking system to simplify future research in robot table tennis or related tracking applications with strong real-time requirements. We evaluate the proposed system thoroughly in simulation and in the real system, outperforming previous work. Furthermore, we show that the accuracy and robustness of the proposed system increases as more cameras are added. Finally, we evaluate the table tennis playing performance of an existing method in the real robot using the proposed vision system. We measure a slight increase in performance compared to a previous vision system even after removing all the heuristics previously present to filter out erroneous ball observations.

Journal or Publication Title: Robotics
Volume of the journal: 8
Issue Number: 4
Publisher: MDPI
Collation: 13 Seiten
Uncontrolled Keywords: object tracking, multiple camera stereo, real-time robotics
Classification DDC: 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 20 Department of Computer Science > Intelligent Autonomous Systems
Date Deposited: 18 Feb 2022 12:08
Last Modified: 02 May 2022 12:07
DOI: 10.26083/tuprints-00015740
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-157402
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/15740
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