An Omnidirectional Vision System for Soccer Robots

This paper describes a complete and efficient vision system developed for the robotic soccer team of the University of Aveiro, CAMBADA (Cooperative Autonomous Mobile roBots with Advanced Distributed Architecture). The system consists on a firewire camera mounted vertically on the top of the robots. A hyperbolic mirror placed above the camera reflects the 360 degrees of the field around the robot. The omnidirectional system is used to find the ball, the goals, detect the presence of obstacles and the white lines, used by our localization algorithm. In this paper we present a set of algorithms to extract efficiently the color information of the acquired images and, in a second phase, extract the information of all objects of interest. Our vision system architecture uses a distributed paradigm where the main tasks, namely image acquisition, color extraction, object detection and image visualization, are separated in several processes that can run at the same time. We developed an efficient color extraction algorithm based on lookup tables and a radial model for object detection. Our participation in the last national robotic contest, ROBOTICA 2007, where we have obtained the first place in the Medium Size League of robotic soccer, shows the effectiveness of our algorithms. Moreover, our experiments show that the system is fast and accurate having a maximum processing time independently of the robot position and the number of objects found in the field.

[1]  Anton Cervin,et al.  Multirate Feedback Control Using the TinyRealTime Kernel , 2004 .

[2]  W. Burgard,et al.  Markov Localization for Mobile Robots in Dynamic Environments , 1999, J. Artif. Intell. Res..

[3]  Giovanni Adorni,et al.  Azzurra Robot Team - ART , 1999 .

[4]  José Santos-Victor,et al.  Toward Robot Perception using Omnidirectional Vision , 2007 .

[5]  Jack Bresenham,et al.  A linear algorithm for incremental digital display of circular arcs , 1977, CACM.

[6]  Armando J. Pinho,et al.  Color-spaces and color segmentation for real-time object recognition in robotic applications , 2007 .

[7]  Colin D. Simpson,et al.  Industrial Electronics , 1936, Nature.

[8]  Armando J. Pinho,et al.  Enhancing the Reactivity of the Vision Subsystem in Autonomous Mobile Robots Using Real-Time Techniques , 2005, RoboCup.

[9]  Jack Bresenham,et al.  Algorithm for computer control of a digital plotter , 1965, IBM Syst. J..

[10]  Luís Seabra Lopes,et al.  An Adaptive TDMA Protocol for Soft Real-Time Wireless Communication among Mobile Autonomous Agents , 2004 .

[11]  Hermann Kopetz,et al.  Real-time systems , 2018, CSC '73.

[12]  Sabine Schulze Robocup 2003 Robot Soccer World Cup Vii , 2003 .

[13]  Andreas Zell,et al.  Tracking Dynamic Objects in a RoboCup Environment - The Attempto T ubingen Robot Soccer Team , 2003 .

[14]  Jan Hoffmann,et al.  A Vision Based System for Goal-Directed Obstacle Avoidance , 2004, RoboCup.

[15]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[16]  Luís Seabra Lopes,et al.  Coordinating Distributed Autonomous Agents with a Real-Time Database: The CAMBADA Project , 2004, ISCIS.

[17]  José Alberto Fonseca,et al.  The FTT-CAN protocol: why and how , 2002, IEEE Trans. Ind. Electron..

[18]  Robert L. Williams,et al.  Mechanical Design and Modeling of an Omni-directional RoboCup Player , 2001 .

[19]  Andreas Zell,et al.  Fast and Accurate Environment Modelling using Omnidirectional Vision , 2004 .