Email this article A Client/Server Message Oriented Middleware for Mobile Robots
Abstract
Mobile robots offer a wide range of applications in educational and research fields. Sensing, planning, control, reasoning, and learning are human-like capabilities that can be artificially replicated in a computer-based robotic system as software applications. The development of software for mobile robot application is a complex task due to the fact that the wide range of robots are composed of heterogeneous hardware components which need different device software drivers and different low-level communication protocols. This paper presents a Client/Server Message Oriented Middle for Mobile Robots which separates the user application from the hardware and low-level implementation. The middleware has been already ported to two different robotic platforms. As a case study, a path planning and self-localization algorithms have been implemented and applied successfully.
Keywords
References
[1] Makarenko A., Brooks A. and Kaupp T., "Orca: Components for Robotics," In International Conference on Intelligent Robots and Systems (IROS), pp. 163-168, Oct. 2006.
[2] Brugali, D. and Prassler, E., "Software Engineering for Robotics [From the Guest Editors]," Robotics & Automation Magazine, IEEE, vol.16, no.1, pp.9-15, March 2009. doi: 10.1109/MRA.2009.932127.
http://dx.doi.org/10.1109/MRA.2009.932127
[3] Chella, M. T., Robotic tool with Scratch Language. In: Robocontrol 2010 4th Workshop in Applied Robotics and Automation, 2010, Bauru. Robocontrol 2010 4th Workshop in Applied Robotics and Automation. Bauru : UNESP. 2010.
[4] Cormen, T.H., C.E. Leiserson, R.L. Rivest and C. Stein, Introduction to Algorithms, Section 22.2: Breadth-First Search. 2nd Edn., MIT Press, McGraw-Hill, New York. 2001.
[5] Crous, C. B., Autonomous robot path Planning (Master's thesis). 2009. URL: http://www.cs.sun.ac.za/~abvdm/mhp/CarlCrous.pdf, July 2011.
[6] Dinh, H. and Inanc, T., Low cost mobile Robotics Experiment with camera and sonar Sensors. In: ACC’09: Proc. of the 2009 Conference on American Control. pp. 3793–3798. IEEE Press. 2009.
http://dx.doi.org/10.1109/ACC.2009.5160449
[7] Eggert, D., Using the Lego Mindstorms NXT robot kit in an Introduction to C Programming class. Journal of Computing Sciences in Colleges 24(6), 8–10. 2009.
[8] Gasperi, M.; Hurbain, P. and Hurbain, I., Extreme NXT : Extending the LEGO Mindstorms NXT to the next level.[S.l.]: Apress. 2007.
[9] Lee, T., Real-Time Face Detection and Recognition on LEGO Mindstorms NXT Robot. Advances in Biometrics 4642, 1006–1015. 2007.
[10] LEGO. Lego Mindstorms NXT. URL: http://mindstorms.lego.com/en-us/default.aspx, July; 2011.
[11] Kranz, M., Rusu, R., Maldonado, A., Beetz, M. and Schmidth, A., "A Player/Stage system for Context-Aware Intelligent Environments," in Proc. of the System Support for Ubiquitous Computing Workshop (UbiSys), Sep. 2006.
[12] McNally, M. and Klassner, F., Demonstrating the Capabilities of MindStorms NXT for the AI Curriculum. In: American Association for Artificial Intelligence. 2007.
[13] Mohamed, N., Al-Jaroodi, J. and Jawhar, I., "Middleware for Robotics: A Survey," Robotics, Automation and Mechatronics, 2008 IEEE Conference on, vol., no., pp.736-742, 21-24 Sept. 2008 doi: 10.1109/RAMECH.2008.4681485.
[14] Ando, N., Suehiro, T., Kitagaki, K., Kotoku, T. and Yoon, W., "RTMiddleware: Distributed Component Middleware for RT (Robot Technology), IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3555-3560, Aug. 2006.
[15] Magnenat, S., Longchamp, V. and Mondada, F., "ASEBA, an event-based middleware for distributed robot control" Workshops DVD of International Conference on Intelligent Robots and Systems (IROS), Oct.-Nov. 2007.
[16] Solano-Aragón, C. and Alanis, A., A Multi-agent Architecture for Controlling Autonomous mobile robots using fuzzy logic and Obstacle Avoidance with Computer vision. Bio-inspired Hybrid Intell. Systems for Image Analysis and Pattern Recognition pp. 215–246 . 2009.
[17] Stevenson, D.E. and Schwarzmeier, J.D., Building an Autonomous Vehicle by Integrating lego Mindstorms and a web cam. In: SIGCSE ’07: Proc. of the 38th SIGCSE technical symposium on Computer science education. pp. 165–169. ACM . 2007.
[18] Talaga, P. and Oh, J., Combining AIMA and LEGO Mindstorms in an Artificial Intelligence course to build real world robots. Journal of Computing Sciences in Colleges 24(3), 56–64. 2009.
[19] Thrun, S., Burgard, W. and Fox, D, Probabilistic Robotics, Section 2.4: Bayes Filters and Section 8.3: Monte Carlo. 2000.
[20] Thrun, S., Fox, D., Burgard, W. and Dellaert, F. Robust monte carlo Localization for mobile robots. Artificial Intelligence, 101:99-141 18. 2000.
[21] Tribelhorn, B. and Dodds, Z.: Evaluating the Roomba: A low-cost, Ubiquitous Platform for Robotics Research and Education. In: 2007 IEEE Int. Conf. on Robotics and Automation. pp. 1393–1399, 2007.
http://dx.doi.org/10.1109/ROBOT.2007.363179
[22] Utz, H., Sablatnog, S., Enderle, S. and Kraetzschmar, G., "Miro - Middleware for mobile robot applications, "Robotics and Automation, IEEE Transactions on, vol.18, no.4, pp. 493- 497. 2002. doi: 10.1109/TRA.2002.802930.
http://dx.doi.org/10.1109/TRA.2002.802930
[23] ZigBee, Digi International [Online]. URL: http://www.digi.com/, July 2011.
Full Text: PDF