Journal of Intelligent & Robotic Systems

, Volume 80, Supplement 1, pp 205–223 | Cite as

Uncertainty-Aware Arm-Base Coordinated Grasping Strategies for Mobile Manipulation

  • Dong Chen
  • Ziyuan Liu
  • Georg von Wichert


The ability to reliably perform grasping operations is key for successful applications of mobile manipulation robots. While robots robustly perform in controlled environment like factories, humans still significantly outperform robots in unconstrained environments. This is particularly true when it comes grasping. Human grasping is faster and tremendously more robust, especially in the presence of significant uncertainty. We aim at improving this situation and propose two major building blocks. Firstly, we consider how to effectively use the mobility of the robot base. Secondly, we show an approach to effectively handle grasping uncertainty. In this paper, we introduce a general system architecture for mobile manipulators to execute grasping tasks. This architecture allows a mobile manipulator to employ arm-base coordinated motions during grasping. The architecture also supports the active handling of uncertainty by means of adaptive grasp strategies. To purposefully handle uncertainty we propose two versatile grasping strategies. Small uncertainty can be directly handled by a rapid grabbing strategy, while large uncertainty can be handled by means of pre-grasp manipulation. The targeted selection of the strategy for a specific case takes both grasp success probability and execution time into consideration. We evaluate our approach on a real robot to show that our approach is feasible in real applications, and that it outperforms a traditional grasping procedure.


Arm-base coordination Grasping under uncertainty Mobile manipulation 


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  1. 1.
    Bohg, J., Morales, A., Asfour, T., Kragic, D.: Data-Driven Grasp Synthesis - A Survey. Robot. IEEE Trans. on 30(2), 289–309 (2014). doi: 10.1109/TRO.2013.2289018 CrossRefGoogle Scholar
  2. 2.
    Chen, D., Liu, Z., von Wichert, G.: Grasping on the move: A generic arm-base coordinated grasping pipeline for mobile manipulation. In: Mobile Robots (ECMR), 2013 European Conference on, pp. 349–354 (2013), doi: 10.1109/ECMR.2013.6698866
  3. 3.
    Chitta, S., Cohen, B., Likhachev, M.: Planning for autonomous door opening with a mobile manipulator. In: Robotics and Automation (ICRA), 2010 IEEE International Conference on, pp. 1799–1806 (2010), doi: 10.1109/ROBOT.2010.5509475
  4. 4.
    Ciocarlie, M., Hsiao, K., Jones, E.G., Chitta, S., Rusu, R.B., Sucan, I.A.: Towards Reliable Grasping and Manipulation in Household Environments. In: Intl. Symposium on Experimental Robotics (ISER) (2010)Google Scholar
  5. 5.
    Diankov, R., Kuffner, J.: Openrave: A planning architecture for autonomous robotics. Robotics Institute, Pittsburgh, PA, Tech. Rep, CMU-RI-TR-08-34 p. 79 (2008)Google Scholar
  6. 6.
    Dietrich, A., Wimbock, T., Albu-Schaffer, A.: Dynamic whole-body mobile manipulation with a torque controlled humanoid robot via impedance control laws. In: Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pp. 3199–3206 (2011), doi: 10.1109/IROS.2011.6094445
  7. 7.
    Dogar, M.: Push-Grasping with Dexterous Hands: Mechanics and a Method (2010)Google Scholar
  8. 8.
    Dogar, M., Srinivasa, S.: A Framework for Push-Grasping in Clutter (2011)Google Scholar
  9. 9.
    Graf, B., Reiser, U., Hagele, M., Mauz, K., Klein, P.: Robotic home assistant Care-O-bot 3-product vision and innovation platform (2009)Google Scholar
  10. 10.
    Hsiao, K., Ciocarlie, M., Brook, P.: Bayesian grasp planning. In: ICRA, 2011 Workshop on Mobile Manipulation Integrating Perception and Manipulation (2011)Google Scholar
  11. 11.
    Hsiao, K., Kaelbling, L.P., Lozano-Perez, T.: Grasping pomdps. In: Robotics and Automation, 2007 IEEE International Conference on, pp. 4685–4692. IEEE (2007)Google Scholar
  12. 12.
    Jiang, L.T., Smith, J.R.: Seashell effect pretouch sensing for robotic grasping. In: Robotics and Automation (ICRA), 2012 IEEE International Conference on, pp. 2851–2858. IEEE (2012)Google Scholar
  13. 13.
    Kazemi, M., Valois, J.S., Bagnell, J.A., Pollard, N.: Robust Object Grasping using Force Compliant Motion Primitives. In: Proceedings of Robotics: Science and Systems Sydney, Australia (2012)Google Scholar
  14. 14.
    Kehoe, B., Berenson, D., Goldberg, K.: Toward cloud-based grasping with uncertainty in shape: Estimating lower bounds on achieving force closure with zero-slip push grasps (2012)Google Scholar
  15. 15.
    Khatib, O., Yokoi, K., Chang, K., Ruspini, D., Holmberg, R., Casal, A.: Vehicle/arm coordination and multiple mobile manipulator decentralized cooperation. In: Intelligent Robots and Systems ’96, IROS 96, Proceedings of the 1996 IEEE/RSJ International Conference on, vol. 2, pp. 546–553 (1996), doi: 10.1109/IROS.1996.570849
  16. 16.
    Koenig, N., Howard, A.: Design and use paradigms for gazebo, an open-source multi-robot simulator. In: Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on, vol. 3, pp. 2149–2154. IEEE (2004)Google Scholar
  17. 17.
    Larsen, E., Gottschalk, S., Lin, M.C., Manocha, D.: Fast proximity queries with swept sphere volumes. University of North Carolina (1999)Google Scholar
  18. 18.
    Liegeois, A.: Automatic supervisory control of the configuration and behavior of multibody mechanisms. IEEE Trans. Syst. Man Cybern. 7(12), 868–871 (1977)MATHCrossRefGoogle Scholar
  19. 19.
    Nakanishi, J., Cory, R., Mistry, M., Peters, J., Schaal, S.: Comparative experiments on task space control with redundancy resolution. In: Intelligent Robots and Systems, 2005.(IROS 2005). 2005 IEEE/RSJ International Conference on, pp. 3901–3908. IEEE (2005)Google Scholar
  20. 20.
    Omrcen, D., Lajpah, L., Nemec, B., Babi, J.: Torque-Velocity Control of Mobile Manipulator in Unstructured Environment. In: RAAD 03 12th International Workshop on Robotics in Alpe-Adria-Danube Region (2003)Google Scholar
  21. 21.
    Ott, C., Bäuml, B., Borst, C., Hirzinger, G.: Employing cartesian impedance control for the opening of a door: A case study in mobile manipulation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, Workshop on mobile manipulators: Basic techniques, new trends applications (2005)Google Scholar
  22. 22.
    Pastor, P., Kalakrishnan, M., Righetti, L., Schaal, S.: Towards Associative Skill Memories. In: Humanoid Robots (Humanoids), 2012 12th IEEE-RAS International Conference on, pp. 309–315 (2012), doi: 10.1109/HUMANOIDS.2012.6651537
  23. 23.
    Pastor, P., Righetti, L., Kalakrishnan, M., Schaal, S.: Online movement adaptation based on previous sensor experiences. In: Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pp. 365–371 IEEE (2011)Google Scholar
  24. 24.
    Puterman, M.L.: Markov decision processes, 2nd edn., pp 331–434 (1990)Google Scholar
  25. 25.
    Roa, M.A., Suárez, R.: Computation of independent contact regions for grasping 3-d objects. Robot. IEEE Trans. on 25, 839–850 (2009)CrossRefGoogle Scholar
  26. 26.
    Sánchez, G., Latombe, J.C.: A single-query bi-directional probabilistic roadmap planner with lazy collision checking (2003)Google Scholar
  27. 27.
    Schaal, S., Peters, J., Nakanishi, J., Ijspeert, A.: Learning movement primitives. In: Robotics Research, pp. 561–572. Springer (2005)Google Scholar
  28. 28.
    Zacharias, F., Borst, C., Hirzinger, G.: Capturing robot workspace structure: representing robot capabilities. In: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on, pp. 3229–3236. IEEE (2007),  10.1109/IROS.2007.4399105
  29. 29.
    Zito, C., Kopicki, M.S., Stolkin, R., Borst, C., Schmidt, F., Roa, M.A., Wyatt, J.L.: Sequential trajectory re-planning with tactile information gain for dexterous grasping under object-pose uncertainty. In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, pp. 4013–4020. IEEE (2013)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Chair of Automatic Control EngineeringTechnische Universität MünchenMunichGermany
  2. 2.Corporate TechnologyMunichGermany

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