Alexander Schaub
German Aerospace Center, Robotics and Mechatronics Center, Weßling, Germnay
Matthias Hellerer
German Aerospace Center, Robotics and Mechatronics Center, Weßling, Germnay
Tim Bodenmüller
German Aerospace Center, Robotics and Mechatronics Center, Weßling, Germnay
Ladda ner artikelhttp://dx.doi.org/10.3384/ecp12076339Ingår i: Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany
Linköping Electronic Conference Proceedings 76:35, s. 339-346
Publicerad: 2012-11-19
ISBN: 978-91-7519-826-2
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
This paper introduces a scheme for testing artificial intelligence algorithms of autonomous systems using Modelica and the DLR Visualization Library. The simulation concepts follows the ’Software-in-the-loop’ principle; whereas no adaptations are made to the tested algorithms. The environment is replaced by an artificial world and the rest of the autonomous system is modeled in Modelica. The scheme is introduced and explained by using the example of the ROboMObil; which is a robotic electric vehicle developed by the DLR’s Robotics and Mechatronics Center.
Simulation of Artificial Intelligence Agents; Autonomous Systems; Software-in-the-Loop; DLR Visualization Library; ROboMObil
[1] Jonathan Brembeck; Lok Man Ho; Alexander Schaub; Clemens Satzger; and Gerhard Hirzinger. Romo - the robotic electric vehicle. In 22nd International Symposium on Dynamics of Vehicle on Roads and Tracks. IAVSD; 2011.
[2] Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall; third edition; December 2009.
[3] B. Gerkey; R. Vaughan; and A. Howard. The player/stage project: Tools for multi-robot and distributed sensor systems. In 11th International Conference on Advanced Robotics (ICAR 2003); Coimbra; Portugal; June 2003.
[4] N. Koenig and A. Howard. Design and use paradigms for gazebo; an open-source multirobot simulator. In Intelligent Robots and Systems; 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on; volume 3; pages 2149 – 2154 vol.3; sept.-2 oct. 2004.
[5] Morgan Quigley; Ken Conley; Brian P. Gerkey; Josh Faust; Tully Foote; Jeremy Leibs; Rob Wheeler; and Andrew Y. Ng. Ros: an opensource robot operating system. In ICRA Workshop on Open Source Software; 2009.
[6] J. Jackson. Microsoft robotics studio: A technical introduction. Robotics Automation Magazine; IEEE; 14(4):82 –87; dec. 2007.
doi: 10.1109/M-RA.2007.905745.
[7] Marc Freese; Surya P. N. Singh; Fumio Ozaki; and Nobuto Matsuhira. Virtual robot experimentation platform v-rep: A versatile 3d robot simulator. In Noriaki Ando; Stephen Balakirsky; Thomas Hemker; Monica Reggiani; and Oskar von Stryk; editors; SIMPAR; volume 6472 of Lecture Notes in Computer Science; pages 51–62. Springer; 2010.
[8] O. Michel. Webots: Professional mobile robot simulation. Journal of Advanced Robotics Systems; 1(1):39–42; 2004.
[9] M. Montemerlo; S. Thrun; and et al. Junior: The stanford entry in the urban challenge. Journal of Field Robotics; 2008.
[10] http://bulletphysics.org - 15.05.2012.
[11] Russell Smith. Open dynamics engine; 2008. http://www.ode.org/.
[12] Tobias Bellmann. Interactive simulations and advanced visualization with modelica. In Proceedings 7th Modelica Conference; Como; Italy; 2009.
[13] Alexander Schaub; Jonathan Brembeck; Darius Burschka; and Gerd Hirzinger. Robotic electric vehicle with camera-based autonomy approach. ATZelektronik; 2(2):10–16; April 2011.
doi: 10.1365/s35658-011-0023-8.
[14] G. Hirzinger and B. Bauml. Agile robot development (ard): A pragmatic approach to robotic software. pages 3741 –3748; oct. 2006.
[15] T. Bodenmuller; W. Sepp; M. Suppa; and G. Hirzinger. Tackling multi-sensory 3d data acquisition and fusion. In Intelligent Robots and Systems; 2007. IROS 2007. IEEE/RSJ International Conference on; pages 2180 –2185; 29 2007-nov. 2 2007.
[16] Charles Poynton. Digital Video and HDTV Algorithms and Interfaces. Morgan Kaufmann Publishers Inc.; San Francisco; CA; USA; 1 edition; 2003.
[17] F. Chaumette and S. Hutchinson. Visual servo control. i. basic approaches. Robotics Automation Magazine; IEEE; 13(4):82 –90; 2006.
doi: 10.1109/MRA.2006.250573.
[18] H. Hirschmuller. Stereo processing by semiglobal matching and mutual information. Pattern Analysis and Machine Intelligence; IEEE Transactions on; 30(2):328 –341; 2008.
[19] Elmar Mair; Gregory D. Hager; Darius Burschka; Michael Suppa; and Gerhard Hirzinger. Adaptive and generic corner detection based on the accelerated segment test. In Proceedings of the 11th European conference on Computer vision: Part II; ECCV’10; pages 183–196; Berlin; Heidelberg; 2010. Springer-Verlag.