Robotics Research pp 305-322

Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 3) | Cite as

On the Dualities Between Grasping and Whole-Body Loco-Manipulation Tasks

  • Tamim Asfour
  • Júlia Borràs
  • Christian Mandery
  • Peter Kaiser
  • Eren Erdal Aksoy
  • Markus Grotz
Chapter

Abstract

Exploiting interaction with the environment is a promising and powerful way to enhance stability of humanoid robots and robustness while executing locomotion and manipulation tasks. This paper revisits several of our works that have a point in common: the exploration of techniques commonly applied in the context of robot grasping with multifingered hands to be applied for whole-body poses during execution of loco-manipulation tasks. Exploiting the fact that the kinematic and dynamic structure of hands holding objects is very similar to the body balancing with multi-contacts, we show how we have defined a taxonomy of whole body poses that provide support to the body, we have used motion data analysis to automatically extract information of detected support poses and the motion transition between them, and we apply the concept of grasp affordances to associate whole-body affordances to an unknown scene. This work provides an overview of our works and proposes directions of promising research direction that is expected to provide meaningful results in the area humanoid robotics in the future.

References

  1. 1.
    Asfour, T., Regenstein, K., Azad, P., Schröder, J., Vahrenkamp, N., Dillmann, R.: ARMAR-III: an integrated humanoid platform for sensory-motor control. In: IEEE/RAS International Conference on Humanoid Robots (Humanoids)Google Scholar
  2. 2.
    Azad, P., Asfour, T., Dillmann, R.: Toward an unified representation for imitation of human motion on humanoids. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 2558–2563 (2007)Google Scholar
  3. 3.
    Berenson, D., Srinivasa, S.S., Kuffner, J.: Task space regions: a framework for pose-constrained manipulation planning. Int. J. Robot. Res. 30(12), 1435–1460 (2011)CrossRefGoogle Scholar
  4. 4.
    Bernardin, K., Ogawara, K., Ikeuchi, K., Dillmann, R.: A sensor fusion approach for recognizing continuous human grasping sequences using hidden markov models. IEEE Trans. Robot. 21(1), 47–57 (2005). doi:10.1109/TRO.2004.833816 CrossRefGoogle Scholar
  5. 5.
    Bicchi, A., Melchiorri, C., Balluchi, D.: On the mobility and manipulability of general multiple limb robots. IEEE Trans. Robot. Autom. 11(2), 215–228 (1995)CrossRefGoogle Scholar
  6. 6.
    Bierbaum, A., Rambow, M., Asfour, T., Dillmann, R.: Grasp affordances from multi-fingered tactile exploration using dynamic potential fields. In: IEEE/RAS International Conference on Humanoid Robots (Humanoids), pp. 168–174 (2009)Google Scholar
  7. 7.
    Borràs, J., Dollar, A.M.: Analyzing dexterous hands using a parallel robots framework. Auton. Robots 36(1–2), 169–180 (2014)CrossRefGoogle Scholar
  8. 8.
    Borràs, J., Dollar, A.M.: Dimensional synthesis of three-fingered robot hands for maximal precision manipulation workspace. Int. J. Robot. Res. 34(14), 1731–1746 (2015)Google Scholar
  9. 9.
    Borràs, J., Asfour, T.: A whole-body pose taxonomy for loco-manipulation tasks. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1578–1585 (2015)Google Scholar
  10. 10.
    Bretl, T., Lall, S.: Testing static equilibrium for legged robots. IEEE Trans. Robot. 24(4), 794–807 (2008)CrossRefGoogle Scholar
  11. 11.
    Ciocarlie, M., Goldfeder, C., Allen, P.: Dimensionality reduction for hand-independent dexterous robotic grasping. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3270–3275 (2007)Google Scholar
  12. 12.
    Collette, C., Micaelli, A., Andriot, C., Lemerle, P.: Robust balance optimization control of humanoid robots with multiple non coplanar grasps and frictional contacts. In: ICRA 2008. IEEE International Conference on Robotics and Automation, pp. 3187–3193. IEEE (2008)Google Scholar
  13. 13.
    Cutkosky, M.R.: On grasp choice, grasp models, and the design of hands for manufacturing tasks. IEEE Trans. Robot. Autom. 5(3), 269279 (1989)CrossRefGoogle Scholar
  14. 14.
    Detry, R., Kraft, D., Kroemer, O., Bodenhagen, L., Peters, J., Krüger, N., Piater, J.: Learning grasp affordance densities. Paladyn J. Behav. Robot. 2(1), 1–17 (2011)CrossRefGoogle Scholar
  15. 15.
    Ebert-Uphoff, I., Voglewede, P., et al.: On the connections between cable-driven robots, parallel manipulators and grasping. IEEE Int. Conf. Robot. Autom. 5, 4521–4526 (2004)Google Scholar
  16. 16.
    Englsberger, J., Ott, C., Albu-Schaffer, A.: Three-dimensional bipedal walking control using divergent component of motion. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2600–2607 (2013)Google Scholar
  17. 17.
    Feix, T., Bullock, I.M., Dollar, A.M.: Analysis of human grasping behavior: object characteristics and grasp type. IEEE Trans. Haptics 7(3), 311–323 (2014)CrossRefGoogle Scholar
  18. 18.
    Feix, T., Pawlik, R., Schmiedmayer, H.B., Romero, J., Kragic, D.: A comprehensive grasp taxonomy. In: Robotics, Science and Systems: Workshop on Understanding the Human Hand for Advancing Robotic Manipulation (2009)Google Scholar
  19. 19.
    Feix, T., Romero, J., Schmiedmayer, H.B., Dollar, A.M., Kragic, D.: The grasp taxonomy of human grasp types. IEEE Trans. Hum.-Mach. Syst. (2015). In pressGoogle Scholar
  20. 20.
    Gibson, J.J.: The Ecological Approach to Visual Perception. Psychology Press, Hove (1979)Google Scholar
  21. 21.
    Huang, H.J., Ahmed, A.A.: Tradeoff between stability and maneuverability during whole-body movements. PLoS One 6(7), e21,815 (2011)Google Scholar
  22. 22.
    Jaillet, L., Porta, J.M.: Path planning under kinematic constraints by rapidly exploring manifolds. IEEE Trans. Robot. 29(1), 105–117 (2013)CrossRefGoogle Scholar
  23. 23.
    Kaiser, P., Gonzalez-Aguirre, D., Schültje, F., Sol, J.B., Vahrenkamp, N., Asfour, T.: Extracting whole-body affordances from multimodal exploration. In: Proceedings of the IEEE-RAS International Conference on Humanoid Robots (2014)Google Scholar
  24. 24.
    Kaiser, P., Grotz, M., Aksoy, E.E., Do, M., Vahrenkamp, N., Asfour, T.: Validation of whole-body loco-manipulation affordances for pushability and liftability. In: IEEE/RAS International Conference on Humanoid Robots (Humanoids) (2015)Google Scholar
  25. 25.
    Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K., Hirukawa, H.: Biped walking pattern generation by using preview control of zero-moment point. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2, p. 16201626 (2003)Google Scholar
  26. 26.
    Kamakura, N.: Te no katachi Te no ugoki. Ishiyaku, Tokyo (1989)Google Scholar
  27. 27.
    Kerr, J., Roth, B.: Analysis of multifingered hands. Int. J. Robot. Res. 4(4), 3–17 (1986)CrossRefGoogle Scholar
  28. 28.
    Krüger, N., Geib, C., Piater, J., Petrick, R., Steedman, M., Wörgötter, F., Ude, A., Asfour, T., Kraft, D., Omrčen, D., Agostini, A., Dillmann, R.: Object-action complexes: grounded abstractions of sensorimotor processes. Robot. Auton. Syst. 59, 740–757 (2011)CrossRefGoogle Scholar
  29. 29.
    Kwon, T., Shin, S.Y.: Motion modeling for on-line locomotion synthesis. In: Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 29–38. ACM (2005)Google Scholar
  30. 30.
    Ma, R.R., Dollar, A.M.: On dexterity and dexterous manipulation. In: 2011 15th International Conference on Advanced Robotics (ICAR), pp. 1–7. IEEE (2011)Google Scholar
  31. 31.
    Mandery, C., Borràs, J., Jochner, M., Asfour, T.: Analyzing whole-body pose transitions in multi-contact motions. In: IEEE/RAS International Conference on Humanoid Robots (Humanoids), pp. 5411–5418 (2015)Google Scholar
  32. 32.
    Mandery, C., Terlemez, O., Do, M., Vahrenkamp, N., Asfour, T.: The KIT whole-body human motion database. In: International Conference on Advanced Robotics (ICAR), pp. 329–336 (2015)Google Scholar
  33. 33.
    Mandery, C., Terlemez, O., Do, M., Vahrenkamp, N., Asfour, T.: Unifying representations and large-scale whole-body motion databases for studying human motion. IEEE Trans. Robot. 32(4), 796–809 (2016)Google Scholar
  34. 34.
    Mason, M.T.: Chapter 4.3 Kinematic models of contact. Mechanics of Robotic Manipulation, pp. 86–88. The MIT Press, Cambridge (2001)Google Scholar
  35. 35.
    Mason, M.T.: Mechanics of Robotic Manipulation. MIT Press, Cambridge (2001)Google Scholar
  36. 36.
    Nakamura, Y.: Grasp and manipulation. J. Meas. Control 29(3), 206–212 (1990) (Japanese)Google Scholar
  37. 37.
    Nakamura, Y., Nagai, K., Yoshikawa, T.: Dynamics and stability in coordination of multiple robotic mechanisms. Int. J. Robot. Res. 8(2), 44–61 (1989)CrossRefGoogle Scholar
  38. 38.
    Nori, F., Peters, J., Padois, V., Babic, J., Mistry, M., Ivaldi, S.: Whole-body motion in humans and humanoids. In: Workshop on New Research Frontiers for Intelligent Autonomous Systems (2014)Google Scholar
  39. 39.
    Orin, D., Oh, S.: Control of force distribution in robotic mechanisms containing closed kinematic chains. J. Dyn. Syst. Meas. Control 103(2), 134–141 (1981)CrossRefGoogle Scholar
  40. 40.
    Pas, A., Platt, R.: Localizing grasp affordances in 3-D points clouds using taubin quadric fitting. In: International Symposium on Experimental Robotics (ISER) (2014)Google Scholar
  41. 41.
    Popovi, M., Kraft, D., Bodenhagen, L., Baeski, E., Pugeault, N., Kragic, D., Asfour, T., Krüger, N.: A strategy for grasping unknown objects based on co-planarity and colour information. Robot. Auton. Syst. 58(5), 551–565 (2010)CrossRefGoogle Scholar
  42. 42.
    Porta, J.M., Ros, L., Bohigas, O., Manubens, M., Rosales, C., Jaillet, L.: The cuik suite: analyzing the motion closed-chain multibody systems. IEEE Robot. Autom. Mag. 21(3), 105–114 (2014)CrossRefGoogle Scholar
  43. 43.
    Saab, L., Ramos, O.E., Keith, F., Mansard, N., Soueres, P., Fourquet, J.Y.: Dynamic whole-body motion generation under rigid contacts and other unilateral constraints. IEEE Trans. Robot. 29(2), 346–362 (2013)Google Scholar
  44. 44.
    Santello, M., Flanders, M., Soechting, J.F.: Postural hand synergies for tool use. J. Neurosci. 18(23), 10105–10115 (1998)Google Scholar
  45. 45.
    Schiebener, D., Ude, A., Asfour, T.: Physical interaction for segmentation of unknown textured and non-textured rigid objects. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 4959–4966 (2014)Google Scholar
  46. 46.
    Terlemez, O., Ulbrich, S., Mandery, C., Do, M., Vahrenkamp, N., Asfour, T.: Master Motor Map (MMM) - framework and toolkit for capturing, representing, and reproducing human motion on humanoid robots. In: IEEE-RAS International Conference on Humanoid Robots (Humanoids), pp. 894–901 (2014)Google Scholar
  47. 47.
    Vahrenkamp, N., Kröhnert, M., Ulbrich, S., Asfour, T., Metta, G., Dillmann, R., Sandini, G.: Simox: A robotics toolbox for simulation, motion and grasp planning. In: International Conference on Intelligent Autonomous Systems (IAS), pp. 585–594 (2012)Google Scholar
  48. 48.
    Wächter, M., Schulz, S., Asfour, T., Aksoy, E., Wörgötter, F., Dillmann, R.: Action sequence reproduction based on automatic segmentation and object-action complexes. In: IEEE/RAS International Conference on Humanoid Robots (Humanoids), pp. 189–195 (2013)Google Scholar
  49. 49.
    Warren, W.H.: Perceiving affordances: visual guidance of stair climbing. J. Expe. Psychol. 10(5), 683–703 (1984)Google Scholar
  50. 50.
    Wieber, P.B.: On the stability of walking systems. In: Proceedings of the International Workshop on Humanoid and Human Friendly Robotics (2002)Google Scholar
  51. 51.
    Winter, D.A.: Biomechanics and Motor Control of Human Movement, 4th edn. Wiley, Hoboken (2009)CrossRefGoogle Scholar
  52. 52.
    Yin, K., Loken, K., van de Panne, M.: Simbicon: simple biped locomotion control. ACM Trans. Gr. 26(3), 105–1–105–10 (2007)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Tamim Asfour
    • 1
  • Júlia Borràs
    • 1
  • Christian Mandery
    • 1
  • Peter Kaiser
    • 1
  • Eren Erdal Aksoy
    • 1
  • Markus Grotz
    • 1
  1. 1.Institute for Anthropomatics and Robotics, Karlsruhe Institute of TechnologyKarlsruheGermany

Personalised recommendations