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Semi-task-dependent and uncertainty-driven world model maintenance

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Abstract

Nearly every task a domestic robot could potentially solve requires a description of the robot’s environment which we call a world model. One problem underexposed in the literature is the maintenance of world models. Rather than on creating a world model, this work focuses on finding a strategy that determines when to update which object in the world model. The decision whether or not to update an object is based on the expected information gain obtained by the update, the action cost of the update and the task the robot performs. The proposed strategy is validated during both simulations and real world experiments. The extended series of simulations is performed to show both the performance gain with respect to a benchmark strategy and the effect of the various parameters. The experiments show the proposed approach on different set-ups and in different environments.

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Notes

  1. http://wiki.ros.org/wire.

References

  • Ahmadi, M. & Stone, P. (2005). Continuous area sweeping: A task definition and initial approach. In Proceedings 12th International Conference on Advanced Robotics, 2005. ICAR’05, (pp. 316–323). IEEE.

  • Ahmadi, M. & Stone, P. (2006). A multi-robot system for continuous area sweeping tasks. In Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006, (pp. 1724–1729). IEEE.

  • Bishop, CM. (2006) Pattern recognition and machine learning. New York: Springer.

  • Boers, Y. Driessen, H. Bagchi, A. & Mandal, P. (2010). Particle filter based entropy. In 13th Conference on Information Fusion (FUSION), 2010 (pp. 1–8). IEEE.

  • Churchill, W. & Newman, P. (2012). Practice makes perfect? managing and leveraging visual experiences for lifelong navigation. In IEEE International Conference on Robotics and Automation (ICRA), 2012, (pp. 4525–4532). IEEE. doi:10.1109/ICRA.2012.6224596.

  • Davison A, & Murray, D. (2002) Simultaneous localization and map-building using active vision. In IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24(7), pp. 865–880. doi:10.1109/TPAMI.2002.1017615.

  • Ekvall, S., Kragic, D., & Jensfelt, P. (2007). Object detection and mapping for service robot tasks. Robotica: International Journal of Information, Education and Research in Robotics and Artificial Intelligence, 25(2), 175–187.

    Google Scholar 

  • Elfring, J. van de Molengraft, M. J. G., Janssen, R. J. M, & Steinbuch, M. (2011). Two level world modeling for cooperating robots using a multiple hypotheses filter. In IEEE International Conference on Robotics and Automation (ICRA), 2011 (pp. 815-820). IEEE.

  • Elfring, J. van den Dries, S. van de Molengraft, R. & Steinbuch, M. (2012). Task-based world model verification. In ICRA 2012 Workshop on Semantic Perception and Mapping for Knowledge-enabled Service Robotics.

  • Elfring, J. van den Dries, S. van de Molengraft, M. & Steinbuch, M. (2013a). Semantic world modeling using probabilistic multiple hypothesis anchoring. Robotics and Autonomous Systems, 61(2), pp. 95–105. doi:10.1016/j.robot.2012.11.005.

  • Elfring, J. Jansen, S. van de Molengraft, R. & Steinbuch, M. (2013b). Active object search exploiting probabilistic object-object relations. In Proceedings of 2013 RoboCup Symposium.

  • Frintrop, S., Rome, E., & Christensen, H. I. (2010). Computational visual attention systems and their cognitive foundations: A survey. ACM Transactions on Applied Perception (TAP), 7(1), 6.

    Google Scholar 

  • Hinterstoisser, S. Holzer, S. Cagniart, C. Ilic, S. Konolige, K. Navab, N. & Lepetit, V. (2011). Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes. In IEEE International Conference on Computer Vision (ICCV), 2011, pp. 858–865. IEEE. doi:10.1109/ICCV.2011.6126326.

  • Joho, D. Senk, M. & Burgard, W. (2011). Learning search heuristics for finding objects in structured environments. Robotics and Autonomous Systems 59(5):319–328. doi:10.1016/j.robot.2011.02.012. Special Issue ECMR 2009.

  • Kalra, N, Stentz, T, & Ferguson, D. (2004). Hoplites: A market framework for complex tight coordination in multi-agent teams. DTIC Document: Technical report

  • Khoshelham, K., & Elberink, S. O. (2012). Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors, 12(2), 1437–1454.

    Article  Google Scholar 

  • Konolige, K. & Bowman, J. (2009). Towards lifelong visual maps. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, (pp. 1156–1163). IEEE. doi:10.1109/IROS.2009.5354121.

  • Mason, J. & Marthi, B. (2012). An object-based semantic world model for long-term change detection and semantic querying. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE.

  • Mason, J. Marthi, B. & Parr, R. (2012). Object disappearance for object discovery. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

  • Milford, M. Wyeth, G. (2010). Persistent navigation and mapping using a biologically inspired slam system. The International Journal of Robotics Research 29(9):1131–1153. doi:10.1177/0278364909340592.

  • Pangercic, D. Tenorth, M. Pitzer, B. Beetzh, M. (2012). Semantic object maps for robotic housework—representation, acquisition and use. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vilamoura.

  • Rasolzadeh, B. Targhi, A. T. & Eklundh, J. O. (2007). An attentional system combining top-down and bottom-up influences. In Attention in cognitive systems. Theories and systems from an interdisciplinary viewpoint, (pp. 123–140). Berlin: Springer

  • Rusu, R. B. Marton, Z. C. Blodow, N. Holzbach, A. & Beetz, M. (2009). 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, St. Louis, MO.

  • Schultz, D., Burgard, W., Fox, D., & Cremers, A. B. (2003). People tracking with mobile robots using sample-based joint probabilistic data association filters. The International Journal of Robotics Research, 22(2), 99–116.

    Article  Google Scholar 

  • Sommerlade, E. Reid, I. (2008). Information-theoretic active scene exploration. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, (pp. 1–7). IEEE.

  • Stachniss, C. (2006). Exploration and mapping with mobile robots. PhD thesis, Department of Computer Science, University of Freiburg.

  • Tenorth M, Kunze L, Jain D, Beetz M (2010) Knowrob-map—knowledge-linked semantic object maps. In 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2010, pp. 430–435. doi:10.1109/ICHR.2010.5686350.

  • Unterholzner, A. Himmelsbach, M. & Wuensche, H. J. (2012). Active perception for autonomous vehicles. In IEEE International Conference on Robotics and Automation (ICRA), 2012, (pp. 1620–1627). doi:10.1109/ICRA.2012.6224879.

  • Whaite, P. & Ferrie, F. (1997). Autonomous exploration: driven by uncertainty. In IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19(3), pp. 193–205. doi:10.1109/34.584097.

  • Xu, T. Chenkov, N. Kuhnlenz, K. & Buss, M. (2009). Autonomous switching of top-down and bottom-up attention selection for vision guided mobile robots. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, (pp. 4009–4014). IEEE. doi:10.1109/IROS.2009.5354674.

  • Xu, T. Kühnlenz, K. & Buss, M. (2010). Autonomous behavior-based switched top-down and bottom-up visual attention for mobile robots. IEEE Transactions on Robotics 26(5), 94–954. doi:10.1109/TRO.2010.2062571.

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Acknowledgments

The research leading to these results has received funding from the European Union Seventh Framework Program FP7/2007-2013 under Grant agreement No. 248942 RoboEarth. We would like to thank the anonymous reviewers for their useful comments and valuable feedback.

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Authors and Affiliations

  1. Eindhoven University of Technology, 5600 MB , Eindhoven, The Netherlands

    Jos Elfring, René van de Molengraft & Maarten Steinbuch

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  1. Jos Elfring
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  2. René van de Molengraft
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  3. Maarten Steinbuch
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Correspondence to Jos Elfring.

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Elfring, J., van de Molengraft, R. & Steinbuch, M. Semi-task-dependent and uncertainty-driven world model maintenance. Auton Robot 38, 1–15 (2015). https://doi.org/10.1007/s10514-014-9393-0

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