Reliable Real-Time Ball Tracking for Robot Table Tennis

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 track...

Full description

Bibliographic Details
Main Authors: Sebastian Gomez-Gonzalez, Yassine Nemmour, Bernhard Schölkopf, Jan Peters
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Robotics
Subjects:
Online Access:https://www.mdpi.com/2218-6581/8/4/90
id doaj-6c770fc9abf5401b99a5f49fc16be503
record_format Article
spelling doaj-6c770fc9abf5401b99a5f49fc16be5032020-11-25T01:31:34ZengMDPI AGRobotics2218-65812019-10-01849010.3390/robotics8040090robotics8040090Reliable Real-Time Ball Tracking for Robot Table TennisSebastian Gomez-Gonzalez0Yassine Nemmour1Bernhard Schölkopf2Jan Peters3Max Planck for Intelligent Systems, Max Planck Ring 4, 72072 Tübingen, GermanyMax Planck for Intelligent Systems, Max Planck Ring 4, 72072 Tübingen, GermanyMax Planck for Intelligent Systems, Max Planck Ring 4, 72072 Tübingen, GermanyMax Planck for Intelligent Systems, Max Planck Ring 4, 72072 Tübingen, GermanyRobot 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.https://www.mdpi.com/2218-6581/8/4/90object trackingmultiple camera stereoreal-time robotics
collection DOAJ
language English
format Article
sources DOAJ
author Sebastian Gomez-Gonzalez
Yassine Nemmour
Bernhard Schölkopf
Jan Peters
spellingShingle Sebastian Gomez-Gonzalez
Yassine Nemmour
Bernhard Schölkopf
Jan Peters
Reliable Real-Time Ball Tracking for Robot Table Tennis
Robotics
object tracking
multiple camera stereo
real-time robotics
author_facet Sebastian Gomez-Gonzalez
Yassine Nemmour
Bernhard Schölkopf
Jan Peters
author_sort Sebastian Gomez-Gonzalez
title Reliable Real-Time Ball Tracking for Robot Table Tennis
title_short Reliable Real-Time Ball Tracking for Robot Table Tennis
title_full Reliable Real-Time Ball Tracking for Robot Table Tennis
title_fullStr Reliable Real-Time Ball Tracking for Robot Table Tennis
title_full_unstemmed Reliable Real-Time Ball Tracking for Robot Table Tennis
title_sort reliable real-time ball tracking for robot table tennis
publisher MDPI AG
series Robotics
issn 2218-6581
publishDate 2019-10-01
description 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.
topic object tracking
multiple camera stereo
real-time robotics
url https://www.mdpi.com/2218-6581/8/4/90
work_keys_str_mv AT sebastiangomezgonzalez reliablerealtimeballtrackingforrobottabletennis
AT yassinenemmour reliablerealtimeballtrackingforrobottabletennis
AT bernhardscholkopf reliablerealtimeballtrackingforrobottabletennis
AT janpeters reliablerealtimeballtrackingforrobottabletennis
_version_ 1725085950756782080