Abstract
This work presents a realistic simulator called Reality Sim for humanoid soccer robots especially in simulation of computer vision. As virtual training, testing and evaluating environment, simulation platforms have become one significant component in Soccer Robot projects. Nevertheless, the simulated environment in a simulation platform usually has a big gap with the realistic world. In order to solve this issue, we demonstrate a more realistic simulation system which is called Reality Sim with numerous real images. With this system, the computer vision code could be easily tested on the simulation platform. For this purpose, an image database with a large quantity of images recorded in various camera poses is built. Furthermore, if the camera pose of an image is not included in the database, an interpolation algorithm is used to reconstruct a brand-new realistic image of that pose such that a realistic image could be provided on every robot camera pose. Systematic empirical results illustrate the efficiency of the approach while it effectively simulates a more realistic environment for simulation so that it satisfies the requirement of humanoid soccer robot projects.
Based on <Reality Sim: a realistic environment for robot simulation platform of humanoid robot>, by <Yao Fu, Hamid Moballegh, Raúl Rojas, Longxu Jin, Miao Wang> which appeared in the proceedings of the 5th International Conference on Automation, Robotics and Applications (ICARA2011). © 2011 IEEE.
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References
H. Kitano et al. RoboCup: a challenge problem for AI and robotics. RoboCup-97: Robot Soccer World Cup I, (Springer, Heidelberg 1998), pp. 1–19
K. Asanuma, K. Umeda, R. Ueda, T. Arai, in Development of a Simulator of Environment and Measurement for Autonomous Mobile Robots Considering Camera Characteristics. Proceedings of robot soccer world cup VII (Springer, Heidelberg, 2003)
T. Ishimura, T. Kato, K. Oda, T. Ohashi, in An Open Robot Simulator Environment. Proceedings of robot soccer world cup VII (Springer, Heidelberg, 2003)
N. Jakobi, Minimal simulations for evolutionary robotics. PhD thesis, University of Sussex, 1998
Ziemke, On the role of robot simulations in embodied cognitive science. AISB J. 1(4), 389–399 (2003)
M. Young, The Technical Writer’s Handbook. Mill Valley, CA: Juan Cristobal Zagal and Javier Ruiz-del-Solar. Combining simulation and reality in evolutionary robotics. J. Intell. Robot Syst. 50(1), 19–39 (2007)
J.C. Zagal, J. Ruiz-del-Solar, in UCHILSIM: A Dynamically and Visually Realistic Simulator for the RoboCup Four Legged League, vol. 3276 . RoboCup 2004: Robot soccer world cup VII, lecture notes in computer science (Springer, Berlin, 2004), pp. 34–45
J.C. Zagal, J. Ruiz-del-Solar, P. Vallejos, in Back-to-Reality: Crossing the Reality Gap in Evolutionary Robotics. IAV 2004: Proceedings 5th IFAC symposium on intelligent autonomous Vehicles, Elsevier Science Publishers B.V. AISB J. 1(4), 389–399 (2004)
J.C. Bongard, H. Lipson, in Once More Unto the Breach: Co–Evolving a Robot and its Simulator. Proceedings of the ninth international conference on the simulation and synthesis of living systems (ALIFE9), pp. 57–62
L. Iocchi, F. Dalla Libera, E. Menegatti, in Learning Humanoid Soccer Actions Interleaving Simulated and Real Data. Proceedings of the second workshop on humanoid soccer robots IEEE-RAS 7th international conference on humanoid robots, Pittsburgh, 2007
B Fischer et al. FUmanoid team description paper 2010. (Workshop Robocup Singapore 2010)
S. Thrun, D. Fox, W. Burgard, F. Dellaert. Robust Monte Carlo localization for mobile robots. Artif. Intell. 128(1–2), 99-141 (2001)
R.E. Kalman, A new approach to linear filtering and predictionproblems. J. Basic Eng. 82(1), 35–45 (1960)
M.J. Quinlan, R.H. Middleton, in Comparison of Estimation Techniques Using Kalman Filter and Grid-Based Filter for Linear and Non-Linear System. Proceedings of the international conference on computing: Theory and applications technique for RoboCup soccer (ICCTA2007) (1960)
M.J. Quinlan, R.H. Middleton. Multiple model kalman filters: a localization technique for RoboCup soccer. Lect. Notes Comput. Sci. 5949, 276–287 (2010)
S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics (MIT Press, Cambridge, 2005)
A.De Doucet, N. Freitas, N.J. Gordon, Sequential Monte Carlo Methods in Practice (Springer, Heidelberg, 2001)
M.S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, A tutorial on particle filters for on line nonlinear/non-gaussian bayesian tracking. IEEE Trans. Sig. Process. 50(2) (2002)
T. Laue, T. Röfer, in Pose Extraction from Sample Sets in Robot Self-localization-a Comparison and a Novel Approach. Proceedings of the 4th European conference on mobile robots—ECMR’09, (Mlini/Dubrovnik, Croatia, 2009), pp. 283–288
T. Langner, Selbstlokalisierung für humanoide Fußballroboter mittels Mono-und Stereovision. Master thesis. FU Berlin, FB Mathematik und Informatik, Berlin. September 2009 (in German)
R. Douc, O. Cappe, E. Moulines, in Comparison of Resampling Schemes for Particle Filtering. ISPA 2005. Proceedings of the 4th international symposium on image and signal processing and analysis (2005), pp. 64–69
A. Desrosières, The Politics of Large Numbers: a History of Statistical Reasoning, Trans. Camille Naish (Harvard University Press, United State, 2004)
A. Björck, Numerical Methods for Least Squares Problems (SIAM, Philadelphia, 1996)
J. Nocedal, J. Stephen, Wright Numerical Optimization (Springer, Heidelberg, 1999)
D. Serfert et al. FUmanoid team description paper 2011. Workshop RoboCup Istanbul (2011)
RoboCup soccer humanid league rules and setup, http://www.tzi.de/humanoid/bin/view/Website/Downloads
Acknowledgments
The authors gratefully acknowledge Daniel Seifert for his knowledge of the project and other members of FUmanoid Team for providing the software base for this work. A video which is relevant to the chapter is linked: http://www.youtube.com/watch?v=TjjBYVMxZak.
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Fu, Y., Moballegh, H., Rojas, R., Jin, L., Wang, M. (2013). A Realistic Simulator for Humanoid Soccer Robot Using Particle Filter. In: Sen Gupta, G., Bailey, D., Demidenko, S., Carnegie, D. (eds) Recent Advances in Robotics and Automation. Studies in Computational Intelligence, vol 480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37387-9_21
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