Abstract
The productivity of groups can be increased by enabling group members to share their perceptions of the environment. We adapt this concept for mobile robots by presenting an object-oriented approach to a shared environmental model. The objects are stored in a graph, which saves memory and computing power and allows the representation of hierarchical and topological relationships. Each object can contain geometric and semantic data as well as information about its current, past, and planned or estimated future movements. An example application shows that modeling future motion can prevent collisions.
Chapter PDF
Similar content being viewed by others
References
1. Chatila, R. & Laumond, J. Position referencing and consistent world modeling for mobile robots in 1985 IEEE International Conference on Robotics and Automation Proceedings 1985 IEEE International Conference on Robotics and Automation Proceedings. 2 (Mar. 1985), 138–145.
2. Durrant-Whyte, H. & Bailey, T. Simultaneous localization and mapping: part I. IEEE Robotics Automation Magazine 13, 99–110 (June 2006).
3. Kohlbrecher, S., Stryk, O. v., Meyer, J. & Klingauf, U. A flexible and scalable SLAM system with full 3D motion estimation in 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics (Nov. 2011), 155–160.
4. Mason, J. & Marthi, B. An object-based semantic world model for long-term change detection and semantic querying in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (Oct. 2012), 3851–3858.
5. Galindo, C. et al. Multi-hierarchical semantic maps for mobile robotics in 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (Aug. 2005), 2278–2283.
6. Marton, Z.-C., Pangercic, D., Blodow, N. & Beetz, M. Combined 2D–3D categorization and classification for multimodal perception systems. The International Journal of Robotics Research 30, 1378–1402 (Sept. 1, 2011).
7. Goerke, N. & Braun, S. Building semantic annotated maps by mobile robots in Proceedings of the conference towards autonomous robotic systems (2009), 149–156.
8. Binder, B. Spatio-temporal prioritized planning Diplomarbeit (Technische Universität Wien, 2017).
9. Coradeschi, S. & Saffiotti, A. Anchoring symbols to sensor data: preliminary report in Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence (2000), 129–135.
10. Baum, M., Ghetţa, I., Belkin, A., Beyerer, J. & Hanebeck, U. D. Data association in a world model for autonomous systems in 2010 IEEE Conference on Multisensor Fusion and Integration 2010 IEEE Conference on Multisensor Fusion and Integration (Sept. 2010), 187–192.
11. Günther, M., Ruiz-Sarmiento, J. R., Galindo, C., González-Jiménez, J. & Hertzberg, J. Context-aware 3D object anchoring for mobile robots. Robotics and Autonomous Systems 110, 12–32. issn: 0921-8890 (Dec. 1, 2018).
12. Fleury, C., Duval, T., Gouranton, V. & Arnaldi, B. A new adaptive data distribution model for consistency maintenance in collaborative virtual environments in. Joint Virtual Reality Conf. of EGVE 2010 - The 16th Eurographics Symposium on Virtual Environments, EuroVR 2010 - The 7th EuroVR (INTUITION) Conf., VEC 2010 - The Annual Virtual Efficiency Congress (2010), 29–36.
13. Singh, G., Serra, L., Png, W., Wong, A. & Ng, H. BrickNet: sharing object behaviors on the Net in Proceedings Virtual Reality Annual International Symposium ʼ95 Proceedings Virtual Reality Annual International Symposium ʼ95 (Mar. 1995), 19–25.
14. Hesina, G., Schmalstieg, D., Furhmann, A. & Purgathofer, W. Distributed open inventor: A practical approach to distributed 3D graphics in Proceedings of the ACM symposium on Virtual reality software and technology (1999), 74–81.
15. Kharitonov, V. Y. A Consistency Model for Distributed Virtual Reality Systems in 2009 Fourth International Conference on Dependability of Computer Systems 2009 Fourth International Conference on Dependability of Computer Systems (June 2009), 271–278.
16. Shaik, N., Liebig, T., Kirsch, C. & Müller, H. in KI 2017: Advances in Artificial Intelligence (eds Kern-Isberner, G., Fürnkranz, J. & Thimm, M.) Lecture Notes in Computer Science 10505, 249–261 (Springer International Publishing, Cham, 2017). isbn: 978-3-319-67189-5.
17. Wurm, K. M., Hornung, A., Bennewitz, M., Stachniss, C. & Burgard, W. OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems in Proc. of the ICRA 2010 workshop on best practice in 3D perception and modeling for mobile manipulation 2 (2010).
18. Wurm, K. M. et al. Hierarchies of octrees for efficient 3D mapping in 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (Sept. 2011), 4249–4255.
19. Gregor, R., Lutzeler, M., Pellkofer, M., Siedersberger, K.-H. & Dickmanns, E. D. EMS-Vision: a perceptual system for autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems 3, 48–59 (Mar. 2002).
20. Blumenthal, S., Bruyninckx, H., Nowak, W. & Prassler, E. A scene graph based shared 3D world model for robotic applications in. Proceedings – IEEE International Conference on Robotics and Automation (2013), 453–460.
21. Ulbrich, S., Nothdurft, T., Maurer, M. & Hecker, P. Graph-based context representation, environment modeling and information aggregation for automated driving in 2014 IEEE Intelligent Vehicles Symposium Proceedings 2014 IEEE Intelligent Vehicles Symposium Proceedings (June 2014), 541–547.
22. Manso, L. J. et al. Deep Representations for Collaborative Robotics in Brain-Inspired Computing (eds Amunts, K., Grandinetti, L., Lippert, T. & Petkov, N.) (Springer International Publishing, 2016), 179–193. isbn: 978-3-319-50862-7.
23. Papp, Z., Brown, C. & Bartels, C. World modeling for cooperative intelligent vehicles in 2008 IEEE Intelligent Vehicles Symposium 2008 IEEE Intelligent Vehicles Symposium (June 2008), 1050–1055.
24. Roth, M., Vail, D. & Veloso, M. A real-time world model for multi-robot teams with high-latency communication in Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453) Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453). 3 (Oct. 2003), 2494–2499.
25. Wiest, J., Höffken, M., Kreßel, U. & Dietmayer, K. Probabilistic trajectory prediction with Gaussian mixture models in 2012 IEEE Intelligent Vehicles Symposium 2012 IEEE Intelligent Vehicles Symposium (June 2012), 141–146.
Acknowledgements
The results presented in this article were developed within the FORobotics (AZ-1225-16) research network. The authors would like to thank the Bavarian Research Foundation and all participating project partners for their funding and support of the project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2020 The Author(s)
About this paper
Cite this paper
Roder, S.Q., Rothmeyer, F., Spiegelberger, B., Reinhart, G. (2020). Development of a Shared Environment Model with Dynamic Trajectory Representation for Multiple Mobile Robots. In: Schüppstuhl, T., Tracht, K., Henrich, D. (eds) Annals of Scientific Society for Assembly, Handling and Industrial Robotics. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-61755-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-662-61755-7_5
Published:
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-61754-0
Online ISBN: 978-3-662-61755-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)