Real-Time Visual Ground-Truth System for Indoor Robotic Applications

The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

[1]  Mac Schwager,et al.  Generating informative paths for persistent sensing in unknown environments , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Roland Siegwart,et al.  A benchmarking tool for MAV visual pose estimation , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

[3]  Andreas Koch,et al.  Advanced Data Logging in RoboCup , 2009, AMS.

[4]  A. Vallat,et al.  Clock Synchronization in Telecommunications via PTP (IEEE 1588) , 2007, 2007 IEEE International Frequency Control Symposium Joint with the 21st European Frequency and Time Forum.

[5]  Manuela M. Veloso,et al.  SSL-Vision: The Shared Vision System for the RoboCup Small Size League , 2009, RoboCup.

[6]  Michael Beetz,et al.  Evaluating Multi-Agent Robotic Systems Using Ground Truth , 2004 .

[7]  Alexander Ferrein,et al.  Providing Ground-Truth Data for the Nao Robot Platform , 2010, RoboCup.

[8]  Prasant Mohapatra,et al.  QRPp1-4: Characterizing Quality of Time and Topology in a Time Synchronization Network , 2006, IEEE Globecom 2006.

[9]  Ferdinand van der Heijden,et al.  Efficient adaptive density estimation per image pixel for the task of background subtraction , 2006, Pattern Recognit. Lett..

[10]  Sidney S. Fels,et al.  Evaluation of Background Subtraction Algorithms with Post-Processing , 2008, 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance.

[11]  André Dias,et al.  Real-Time 3D Ball Trajectory Estimation for RoboCup Middle Size League Using a Single Camera , 2011, RoboCup.

[12]  Jacky Baltes,et al.  RoboCup 2009: Robot Soccer World Cup XIII [papers from the 13th annual RoboCup International Symposium, Graz, Austria, June 29 - July 5, 2009] , 2010, RoboCup.

[13]  D. Robert,et al.  Tracking of flying insects using pan-tilt cameras , 2000, Journal of Neuroscience Methods.

[14]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[15]  Nikolaus Correll,et al.  SwisTrack - a flexible open source tracking software for multi-agent systems , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Peter Stone,et al.  A Low Cost Ground Truth Detection System for RoboCup Using the Kinect , 2011, RoboCup.

[17]  Roland Siegwart,et al.  Collaborative stereo , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Piyush Khandelwal and Peter Stone.  A Low Cost Ground Truth Detection System Using the Kinect , 2011 .

[19]  Kazuya Yoshida,et al.  Collaborative mapping of an earthquake‐damaged building via ground and aerial robots , 2012, J. Field Robotics.

[20]  Jesus Savage,et al.  RoboCup 2011: Robot Soccer World Cup XV , 2012, Lecture Notes in Computer Science.

[21]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..