Abstract
Adaptability to changing environments and environmental conditions is a key concern for future smart applications. Therefore, for autonomous systems it will be necessary to extend the local view on the environment with external sensors, either fixed or mobile ones. New evolving technologies support the acquisition of a myriad of information, described as “Internet of Things”, “Intelligent Environments”, “Industrial or Building Automation”, “Ambient Intelligence”, or “Ubiquitous/Pervasive Computing”, etc. Thus, information is always available, but its interpretation and integration into the own view remains an open problem. We therefore propose the development of a new type of distributed middleware for the environmental perception, that abstracts the environment from the diversity of available sensor systems. In three steps we describe how more and more functionalities can be extracted from the control application to support artificial perception and environment modelling.
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References
Ikfast: The robot kinematics compiler (2012), http://openrave.org/docs/latest_stable/openravepy/ikfast/
Wang, Y., Linnett, J., Roberts, J.: A unified approach to inverse and direct kinematics for four kinds of wheeled mobile robots and its applications. In: Proceedings of the 1996 IEEE International Conference on Robotics and Automation, vol. 4, pp. 3458–3465. IEEE (1996)
Şucan, I.A., Moll, M., Kavraki, L.E.: The Open Motion Planning Library. IEEE Robotics & Automation Magazine (to appear, 2012), http://ompl.kavrakilab.org
Schulze, M., Zug, S.: Exploiting the FAMOUSO Middleware in Multi-Robot Application Development with Matlab/Simulink. In: Proceedings of the ACM/IFIP/USENIX Middleware 2008 Conference Companion, Leuven, Belgium, pp. 74–77. ACM, New York (2008), http://doi.acm.org/10.1145/1462735.1462753
Schulze, M.: Adaptierbare ereignisbasierte Middleware für ressourcenbeschränkte Systeme. Doktorarbeit, Fakultät für Informatik, Otto-von-Guericke Universität Magdeburg (2011)
Zug, S., Dietrich, A., Kaiser, J.: Fault-Handling in Networked Sensor Systems. Concept Press Ltd., St. Franklin (2012)
Zug, S., Dietrich, A.: Examination of Fusion Result Feedback for Fault-Tolerant and Distributed Sensor Systems. In: IEEE International Workshop on Robotic and Sensors Environments (ROSE 2010), Phoenix, AZ, USA (2010)
Zug, S.: Architektur für verteilte, fehlertolerante Sensor-Aktor-Systeme. Doktorarbeit, Fakultät für Informatik, Otto-von-Guericke Universität Magdeburg (2011)
Zug, S., Schulze, M., Dietrich, A., Kaiser, J.: Programming abstractions and middleware for building control systems as networks of smart sensors and actuators. In: Proceedings of Emerging Technologies in Factory Automation (ETFA 2010), Bilbao, Spain (September 2010)
Caulfield, H., Johnson, J.: Artificial perception and consciousness. In: Sixth International Conference on Education and Training in Optics and Photonics, Cancún, Mexico, July 28-30 1999, p. 112. Society of Photo Optical (2000)
Wills, L., Kannan, S., Sander, S., Guler, M., Heck, B., Prasad, J., Schrage, D., Vachtsevanos, G.: An open platform for reconfigurable control. IEEE Control Systems Magazine 21(3), 49–64 (2001)
Hermann, A., Desel, J.: Driving situation analysis in automotive environment. In: IEEE International Conference on Vehicular Electronics and Safety, ICVES 2008, pp. 216–221. IEEE (2008)
Rotenstein, A., Rothenstein, A., Robinson, M., Tsotsos, J.: Robot middleware must support task-directed perception. In: Proc. ICRA 2nd Int. Workshop on Software Development and Integration into Robotics, Rome, Italy (2007)
Hähnel, D., Burgard, W., Thrun, S.: Learning compact 3d models of indoor and outdoor environments with a mobile robot. Robotics and Autonomous Systems 44(1), 15–27 (2003)
Surmann, H., Nüchter, A., Hertzberg, J.: An autonomous mobile robot with a 3d laser range finder for 3d exploration and digitalization of indoor environments. Robotics and Autonomous Systems 45(3), 181–198 (2003)
Rusu, R., Marton, Z., Blodow, N., Dolha, M., Beetz, M.: Towards 3d point cloud based object maps for household environments. Robotics and Autonomous Systems 56(11), 927–941 (2008)
Rusu, R., Marton, Z., Blodow, N., Holzbach, A., Beetz, M.: Model-based and learned semantic object labeling in 3d point cloud maps of kitchen environments. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, pp. 3601–3608. IEEE (2009)
Roy, D., Hsiao, K., Mavridis, N.: Mental imagery for a conversational robot. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34(3), 1374–1383 (2004)
Hsiao, K., Mavridis, N., Roy, D.: Coupling perception and simulation: Steps towards conversational robotics. In: International Conference on Intelligent Robots and Systems, vol. 1, pp. 928–933. IEEE (October 2003)
Cook, D., Das, S.: How smart are our environments? an updated look at the state of the art. Pervasive and Mobile Computing 3(2), 53–73 (2007)
Saffiotti, A., Broxvall, M., Seo, B., Cho, Y.: The peis-ecology project: a progress report. In: Proc. of the ICRA 2007 Workshop on Network Robot Systems, Rome, Italy, pp. 16–22. Citeseer (2007)
Smith, R.L.: The open dynamics engine (2007), http://ode.org
Meeussen, W., Hsu, J., Diankov, R.L.: URDF - Unified Robot Description Format (April 2012), http://www.ros.org/wiki/urdf
Diankov, R.: Automated construction of robotic manipulation programs. Ph.D. dissertation, Carnegie Mellon University, Robotics Institute (October 2010)
Dietrich, A., Zug, S., Kaiser, J.: Detecting External Measurement Disturbances Based on Statistical Analysis for Smart Sensors. In: Procedings of the IEEE International Symposium on Industrial Electronics (ISIE), pp. 2067–2072 (July 2010)
Dietrich, A., Zug, S., Kaiser, J.: Modelbasierte Fehlerdetektion in verteilten Sensor-Aktor-Systemen. In: 11./12. Forschungskolloquium am Fraunhofer IFF. Fraunhofer Institut für Fabrikbetrieb und Automatisierung, IFF (2011)
Dietrich, A., Zug, S., Kaiser, J.: Model based Decoupling of Perception and Processing. In: ERCIM/EWICS/Cyberphysical Systems Workshop, Resilient Systems, Robotics, Systems-of-Systems Challenges in Design, Validation & Verification and Certification, Naples, Italy (September 2011)
Zug, S., Schulze, M., Dietrich, A., Kaiser, J.: Reliable Fault-Tolerant Sensors for Distributed Systems. In: Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems (DEBS 2010), Cambridge, United Kingdom, pp. 105–106. ACM Press, New York (2010)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.: Ros: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3(3.2) (2009)
Foote, T., Marder-Eppstein, E., Meeussen, W.L.: tf - ros (April 2012), http://www.ros.org/wiki/tf
Smith, R.C., Cheeseman, P.: On the Representation and Estimation of Spatial Uncertainty. The International Journal of Robotics Research 5(4), 56–68 (1986)
Dietrich, A., Schulze, M., Zug, S., Kaiser, J.: Visualization of Robot’s Awareness and Perception. In: First International Workshop on Digital Engineering (IWDE), Magdeburg, Germany. ACM Press, New York (2010)
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Dietrich, A., Zug, S., Kaiser, J. (2012). Towards Artificial Perception. In: Ortmeier, F., Daniel, P. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2012. Lecture Notes in Computer Science, vol 7613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33675-1_44
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DOI: https://doi.org/10.1007/978-3-642-33675-1_44
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