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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.
In: Robotics, 2022, 8 (4)
doi: 10.26083/tuprints-00015740
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (Abstract)

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.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Gomez-Gonzalez, Sebastian ; Nemmour, Yassine ; Schölkopf, Bernhard ; Peters, Jan
Art des Eintrags: Zweitveröffentlichung
Titel: Reliable Real-Time Ball Tracking for Robot Table Tennis
Sprache: Englisch
Publikationsjahr: 2022
Publikationsdatum der Erstveröffentlichung: 2022
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Robotics
Jahrgang/Volume einer Zeitschrift: 8
(Heft-)Nummer: 4
Kollation: 13 Seiten
DOI: 10.26083/tuprints-00015740
URL / URN: https://tuprints.ulb.tu-darmstadt.de/15740
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Herkunft: Zweitveröffentlichung
Kurzbeschreibung (Abstract):

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.

Freie Schlagworte: object tracking, multiple camera stereo, real-time robotics
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-157402
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Intelligente Autonome Systeme
Hinterlegungsdatum: 18 Feb 2022 12:08
Letzte Änderung: 21 Feb 2022 11:09
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