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Published in: e & i Elektrotechnik und Informationstechnik 6/2020

26-08-2020 | Originalarbeit

Evaluierung von Navigationsmethoden für mobile Roboter

Authors: Wilfried Wöber, Johannes Rauer, Maximilian Papa, Ali Aburaia, Simon Schwaiger, Georg Novotny, Mohamed Aburaia, Wilfried Kubinger

Published in: e+i Elektrotechnik und Informationstechnik | Issue 6/2020

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Zusammenfassung

Mobile Manipulation ist das Kernstück eines hochflexiblen und autonomen Produktionssystems. Durch vernetzte und roboterbasierte Automatisierung ist eine individuell angepasste Fertigung möglich, wobei mobile Manipulatoren sowohl bei Transportaufgaben als auch bei der Werkstückbereitstellung eine signifikante Rolle spielen. Die Digitale Fabrik der FH Technikum Wien ist eine Forschungs- sowie Lehrplattform und dient der exemplarischen Erprobung neuer Technologien zur digitalen und flexiblen Produktion. Im Zuge mehrerer Forschungsarbeiten wurden mobile Manipulatoren in der Digitalen Fabrik integriert. Basierend darauf und auf einem konkreten und symbolischen Use Case diskutiert diese Arbeit verschiedene Methoden zur Navigation mobiler Manipulatoren. Es werden Positionierungsgenauigkeiten basierend auf unterschiedlichen Navigationsmethoden, Sicherheitsaspekte und Auswirkungen auf die Handhabung von Objekten diskutiert.

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Literature
1.
go back to reference Lehner, F., Schmid, J. (1992): Industrielle Wettbewerbsfähigkeit und flexible Produktionssysteme – Zukunftschancen der Fabrik (S. 13–28). Wiesbaden: VS Verlag für Sozialwissenschaften. Lehner, F., Schmid, J. (1992): Industrielle Wettbewerbsfähigkeit und flexible Produktionssysteme – Zukunftschancen der Fabrik (S. 13–28). Wiesbaden: VS Verlag für Sozialwissenschaften.
2.
go back to reference Westkämper, E., Spath, D., Constantinescu, C., Lentes, L. (2006): Digitale Produktion. Berlin: Springer. Westkämper, E., Spath, D., Constantinescu, C., Lentes, L. (2006): Digitale Produktion. Berlin: Springer.
3.
go back to reference Chebab, Z.-E., Fauroux, J.-C., Bouton, N., Mezouar, Y., Sabourin, L. (2015): Autonomous collaborative mobile manipulators: state of the art. In TrC-IFToMM symposium on theory of machines and mechanisms, Izmir, Turkey. Chebab, Z.-E., Fauroux, J.-C., Bouton, N., Mezouar, Y., Sabourin, L. (2015): Autonomous collaborative mobile manipulators: state of the art. In TrC-IFToMM symposium on theory of machines and mechanisms, Izmir, Turkey.
4.
go back to reference Thrun, S., Burgard, W., Fox, D. (2006): Probabilistic robotics. Cambridge: MIT Press. MATH Thrun, S., Burgard, W., Fox, D. (2006): Probabilistic robotics. Cambridge: MIT Press. MATH
5.
go back to reference Larsen, T. D., Hansen, K. L., Andersen, N. A., Ravn, O. (1999): Design of Kalman filters for mobile robots; evaluation of the kinematic and odometric approach. In Proceedings of the 1999 IEEE international conference on control applications (Cat. No. 99CH36328) (Bd. 2, S. 1021–1026). Larsen, T. D., Hansen, K. L., Andersen, N. A., Ravn, O. (1999): Design of Kalman filters for mobile robots; evaluation of the kinematic and odometric approach. In Proceedings of the 1999 IEEE international conference on control applications (Cat. No. 99CH36328) (Bd. 2, S. 1021–1026).
7.
go back to reference Kia, S. S., Rounds, S. F., Martínez, S. (2014): A centralized-equivalent decentralized implementation of extended Kalman filters for cooperative localization. In 2014 IEEE/RSJ international conference on intelligent robots and systems (S. 3761–3766). Kia, S. S., Rounds, S. F., Martínez, S. (2014): A centralized-equivalent decentralized implementation of extended Kalman filters for cooperative localization. In 2014 IEEE/RSJ international conference on intelligent robots and systems (S. 3761–3766).
8.
go back to reference Fox, D. (2001): Kld-sampling: adaptive particle filters and mobile robot localization. In Advances in neural information processing systems (NIPS). Fox, D. (2001): Kld-sampling: adaptive particle filters and mobile robot localization. In Advances in neural information processing systems (NIPS).
9.
go back to reference Bishop, C. M. (2006): Pattern recognition and machine learning. New York: Springer. MATH Bishop, C. M. (2006): Pattern recognition and machine learning. New York: Springer. MATH
10.
go back to reference Ko, J., Fox, D. (2008): GP-bayesfilters: Bayesian filtering using Gaussian process prediction and observation models. In IEEE/RSJ international conference on intelligent robots and systems, 2008. IROS 2008, Nice, France. New York: IEEE Press. Ko, J., Fox, D. (2008): GP-bayesfilters: Bayesian filtering using Gaussian process prediction and observation models. In IEEE/RSJ international conference on intelligent robots and systems, 2008. IROS 2008, Nice, France. New York: IEEE Press.
11.
go back to reference Reece, S., Roberts, S. (2010): An introduction to Gaussian processes for the Kalman filter expert. In 2010 13th conference on information fusion (FUSION). New York: IEEE Press. Reece, S., Roberts, S. (2010): An introduction to Gaussian processes for the Kalman filter expert. In 2010 13th conference on information fusion (FUSION). New York: IEEE Press.
12.
go back to reference Hartikainen, J., Särkkä, S. (2010): Kalman filtering and smoothing solutions to temporal Gaussian process regression models. In 2010 IEEE international workshop on machine learning for signal processing (MLSP). New York: IEEE Press. MATH Hartikainen, J., Särkkä, S. (2010): Kalman filtering and smoothing solutions to temporal Gaussian process regression models. In 2010 IEEE international workshop on machine learning for signal processing (MLSP). New York: IEEE Press. MATH
13.
go back to reference Grisetti, G., Stachniss, C., Burgard, W. (2005): Improving grid-based SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling. In Proceedings of the IEEE international conference on robotics & automation (ICRA). Grisetti, G., Stachniss, C., Burgard, W. (2005): Improving grid-based SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling. In Proceedings of the IEEE international conference on robotics & automation (ICRA).
14.
go back to reference Labbé, M., Michaud, F. (2018): Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation: Labbé and Michaud. J. Field Robot., 36, 10. Labbé, M., Michaud, F. (2018): Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation: Labbé and Michaud. J. Field Robot., 36, 10.
15.
go back to reference Russell, S., Norvig, P. (2010): Artificial intelligence: a modern approach. Aufl. 3. New York: Prentice Hall. MATH Russell, S., Norvig, P. (2010): Artificial intelligence: a modern approach. Aufl. 3. New York: Prentice Hall. MATH
16.
go back to reference Garrido-Jurado, S., Munoz-Salinas, R., Madrid-Cuevas, F., Marin-Jiménez, M. (2014): Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recognit., 47, 06. Garrido-Jurado, S., Munoz-Salinas, R., Madrid-Cuevas, F., Marin-Jiménez, M. (2014): Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recognit., 47, 06.
17.
go back to reference Goodfellow, I., Bengio, Y., Courville, A. (2016): Deep learning. Cambridge: MIT Press. MATH Goodfellow, I., Bengio, Y., Courville, A. (2016): Deep learning. Cambridge: MIT Press. MATH
18.
go back to reference Pearl, J. (2009): Causality: models, reasoning and inference. Aufl. 2. New York: Cambridge University Press. MATH Pearl, J. (2009): Causality: models, reasoning and inference. Aufl. 2. New York: Cambridge University Press. MATH
19.
go back to reference Pearl, J. (1988): Probabilistic reasoning in intelligent systems: networks of plausible inference. San Francisco: Morgan Kaufmann MATH Pearl, J. (1988): Probabilistic reasoning in intelligent systems: networks of plausible inference. San Francisco: Morgan Kaufmann MATH
21.
go back to reference Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., Fergus, R. (2014): Intriguing properties of neural networks. In International conference on learning representations. [Online] Available: arXiv:1312.6199. Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., Fergus, R. (2014): Intriguing properties of neural networks. In International conference on learning representations. [Online] Available: arXiv:​1312.​6199.
23.
go back to reference Selvaraju, R. R., Das, A., Vedantam, R., Cogswell, M., Parikh, D., Batra, D. (2016): Grad-cam: Why did you say that? visual explanations from deep networks via gradient-based localization. CoRR arXiv:1610.02391. Selvaraju, R. R., Das, A., Vedantam, R., Cogswell, M., Parikh, D., Batra, D. (2016): Grad-cam: Why did you say that? visual explanations from deep networks via gradient-based localization. CoRR arXiv:​1610.​02391.
24.
go back to reference Pearl, J., Mackenzie, D. (2018): The book of why: the new science of cause and effect. Aufl. 1. New York: Basic Books MATH Pearl, J., Mackenzie, D. (2018): The book of why: the new science of cause and effect. Aufl. 1. New York: Basic Books MATH
25.
go back to reference Sattinger, V., Papa, M., Stuja, K., Kubinger, W. (2019): Methodik zur entwicklung sicherer kollaborativer produktionssysteme im rahmen von industrie 4.0. E&I, Elektrotech. Inf.tech., 136, 10. Sattinger, V., Papa, M., Stuja, K., Kubinger, W. (2019): Methodik zur entwicklung sicherer kollaborativer produktionssysteme im rahmen von industrie 4.0. E&I, Elektrotech. Inf.tech., 136, 10.
26.
go back to reference Papa, M., Kaselautzke, D., Stuja, K., Wölfel, W. (2018): Different safety certifiable concepts for mobile robots in industrial environments. In 29TH DAAAM international symposium on intelligent manufacturing and automation (Bd. 01, S. 0791–0800). Papa, M., Kaselautzke, D., Stuja, K., Wölfel, W. (2018): Different safety certifiable concepts for mobile robots in industrial environments. In 29TH DAAAM international symposium on intelligent manufacturing and automation (Bd. 01, S. 0791–0800).
27.
go back to reference Markis, A., Papa, M., Kaselautzke, D., Rathmair, M., Sattinger, V., Brandstötter, M. (2019): Safety of mobile robot systems in industrial applications. In Proceedings of the joint ARW & OAGM workshop (Bd. 05). Markis, A., Papa, M., Kaselautzke, D., Rathmair, M., Sattinger, V., Brandstötter, M. (2019): Safety of mobile robot systems in industrial applications. In Proceedings of the joint ARW & OAGM workshop (Bd. 05).
29.
go back to reference Otrebski, R., Pospisil, D., Engelhardt-Nowitzki, C., Kryvinska, N., Aburaia, M. (2019): Flexibility enhancements in digital manufacturing by means of ontological data modeling. Proc. Comput. Sci., 155, 296–302. The 16th international conference on mobile systems and pervasive computing (MobiSPC 2019), The 14th international conference on future networks and communications (FNC-2019), The 9th international conference on sustainable energy information technology. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S1877050919309573. Otrebski, R., Pospisil, D., Engelhardt-Nowitzki, C., Kryvinska, N., Aburaia, M. (2019): Flexibility enhancements in digital manufacturing by means of ontological data modeling. Proc. Comput. Sci., 155, 296–302. The 16th international conference on mobile systems and pervasive computing (MobiSPC 2019), The 14th international conference on future networks and communications (FNC-2019), The 9th international conference on sustainable energy information technology. [Online]. Available: http://​www.​sciencedirect.​com/​science/​article/​pii/​S187705091930957​3.
30.
go back to reference Rauer, J. N. (2019): Semi-automatic generation of training data for neural networks for 6D pose estimation and robotic grasping. Master’s thesis, University of Applied Sciences Technikum Wien, Vienna, Austria. Rauer, J. N. (2019): Semi-automatic generation of training data for neural networks for 6D pose estimation and robotic grasping. Master’s thesis, University of Applied Sciences Technikum Wien, Vienna, Austria.
31.
go back to reference Rauer, J. N., Wöber, W., Aburaia, M. (2019): An autonomous mobile handling robot using object recognition. In Proceedings of the joint ARW & OAGM workshop (S. 38–43). Rauer, J. N., Wöber, W., Aburaia, M. (2019): An autonomous mobile handling robot using object recognition. In Proceedings of the joint ARW & OAGM workshop (S. 38–43).
32.
go back to reference Parungao, L., Hein, F., Lim, W. (2018): Dijkstra algorithm based intelligent path planning with topological map and wireless communication. J. Eng. Appl. Sci., 13, 04. Parungao, L., Hein, F., Lim, W. (2018): Dijkstra algorithm based intelligent path planning with topological map and wireless communication. J. Eng. Appl. Sci., 13, 04.
33.
go back to reference Quigley, M., Conley, K., Gerkey, B. P., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A. Y. (2009): Ros: an open-source robot operating system. In ICRA workshop on open source software. Quigley, M., Conley, K., Gerkey, B. P., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A. Y. (2009): Ros: an open-source robot operating system. In ICRA workshop on open source software.
34.
go back to reference Kumra, S., Kanan, C. (2017): Robotic grasp detection using deep convolutional neural networks. In IEEE international conference on intelligent robots and systems – IROS (S. 769–776). Kumra, S., Kanan, C. (2017): Robotic grasp detection using deep convolutional neural networks. In IEEE international conference on intelligent robots and systems – IROS (S. 769–776).
35.
go back to reference Tobin, J., Biewald, L., Duan, R., Andrychowicz, M., Handa, A., Kumar, V., McGrew, B., Schneider, J., Welinder, P., Zaremba, W., Abbeel, P. (2017): Domain randomization and generative models for robotic grasping. In IEEE/RSJ international conference on intelligent robots and systems – IROS (S. 3482–3489). Tobin, J., Biewald, L., Duan, R., Andrychowicz, M., Handa, A., Kumar, V., McGrew, B., Schneider, J., Welinder, P., Zaremba, W., Abbeel, P. (2017): Domain randomization and generative models for robotic grasping. In IEEE/RSJ international conference on intelligent robots and systems – IROS (S. 3482–3489).
36.
go back to reference Du, G., Wang, K., Lian, S. (2019): Vision-based robotic grasping from object localization, pose estimation, grasp detection to motion planning: A review. CoRR. Du, G., Wang, K., Lian, S. (2019): Vision-based robotic grasping from object localization, pose estimation, grasp detection to motion planning: A review. CoRR.
37.
go back to reference Fu, M., Zhou, W. (2019): DeepHMap++: combined projection grouping and correspondence learning for full DoF pose estimation. Sensors, 19(5), 1032. Fu, M., Zhou, W. (2019): DeepHMap++: combined projection grouping and correspondence learning for full DoF pose estimation. Sensors, 19(5), 1032.
38.
go back to reference Fischler, M. A., Bolles, R. C. (1981): Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 24(6), 381–395. MathSciNet Fischler, M. A., Bolles, R. C. (1981): Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 24(6), 381–395. MathSciNet
39.
go back to reference Bohg, J., Morales, A., Asfour, T., Kragic, D. (2014): Data-driven grasp synthesis: a survey. IEEE Trans. Robot., 30(2), 289–309. Bohg, J., Morales, A., Asfour, T., Kragic, D. (2014): Data-driven grasp synthesis: a survey. IEEE Trans. Robot., 30(2), 289–309.
40.
go back to reference Tremblay, J., To, T., Sundaralingam, B., Xiang, Y., Fox, D., Birchfield, S. (2018): Deep object pose estimation for semantic robotic grasping of household objects. In 2nd annual conference on robot learning – CoRL (S. 306–316). Tremblay, J., To, T., Sundaralingam, B., Xiang, Y., Fox, D., Birchfield, S. (2018): Deep object pose estimation for semantic robotic grasping of household objects. In 2nd annual conference on robot learning – CoRL (S. 306–316).
41.
go back to reference Steigl, D., Aburaia, M., Wöber, W. (2020): Autonomous grasping of known objects using depth data and the pca. In Proceedings of the joint ARW & OAGM workshop. Steigl, D., Aburaia, M., Wöber, W. (2020): Autonomous grasping of known objects using depth data and the pca. In Proceedings of the joint ARW & OAGM workshop.
42.
go back to reference Andreas, K., Wöber, W. (2020): Vision-based docking of a mobile robot. In Proceedings of the joint ARW & OAGM workshop. Andreas, K., Wöber, W. (2020): Vision-based docking of a mobile robot. In Proceedings of the joint ARW & OAGM workshop.
43.
go back to reference Sutton, R. S., Barto, A. G. (2018): Reinforcement learning: an introduction. Cambridge: MIT Press. MATH Sutton, R. S., Barto, A. G. (2018): Reinforcement learning: an introduction. Cambridge: MIT Press. MATH
Metadata
Title
Evaluierung von Navigationsmethoden für mobile Roboter
Authors
Wilfried Wöber
Johannes Rauer
Maximilian Papa
Ali Aburaia
Simon Schwaiger
Georg Novotny
Mohamed Aburaia
Wilfried Kubinger
Publication date
26-08-2020
Publisher
Springer Vienna
Published in
e+i Elektrotechnik und Informationstechnik / Issue 6/2020
Print ISSN: 0932-383X
Electronic ISSN: 1613-7620
DOI
https://doi.org/10.1007/s00502-020-00820-x

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