A Unified Framework for Whole-Body Humanoid Robot Control with Multiple Constraints and Contacts

  • Oussama Khatib
  • Luis Sentis
  • Jae-Heung Park
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 44)


Physical interactivity is a major challenge in humanoid robot-ics. To allow robots to operate in human environments there is a pressing need for the development of control architectures that provide the advanced capabilities and interactive skills needed to effectively interact with the environment and/or the human partner while performing useful manipulation and locomotion tasks. Such architectures must address the robot whole-body control problem in its most general form: task and whole body motion coordination with active force control at contacts, under various constraints, self collision, and dynamic obstacles. In this paper we present a framework that addresses in a unified fashion the whole-body control problem in the context of multi-point multi-link contacts, constraints, and obstacles. The effectiveness of this novel formulation is illustrated through extensive robot dynamic simulations conducted in SAI, and the experimental validation of the framework is currently underway on the ASIMO platform.


Humanoid Robot Humanoid Robotic Sinusoidal Trajectory Active Force Control Kinetic Energy Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Khatib, O., Sentis, L., Park, J.H., Warren, J.: Whole body dynamic behavior and control of human-like robots. International Journal of Humanoid Robotics 1(1), 29–43 (2004)CrossRefGoogle Scholar
  2. 2.
    Sentis, L., Khatib, O.: Synthesis of whole-body behaviors through hierarchical control of behavioral primitives. International Journal of Humanoid Robotics 2(4), 505–518 (2005)CrossRefGoogle Scholar
  3. 3.
    Park, J., Khatib, O.: A haptic teleoperation approach based on contact force control. International Journal of Robotics Research 25(5), 575–591 (2006)CrossRefGoogle Scholar
  4. 4.
    Hirai, K., Hirose, M., Haikawa, Y., Takenaka, T.: The development of Honda humanoid robot. In: Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium, vol. 2, pp. 1321–1326 (1998)Google Scholar
  5. 5.
    Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K., Hirukawa, H.: Resolved momentum control: Humanoid motion planning based on the linear and angular momentum. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, USA, October 2003, pp. 1644–1650 (2003)Google Scholar
  6. 6.
    Khatib, O., Thaulaud, P., Park, J.: Torque-position transformer for task control of position controlled robots. Patent, Patent Number: 20060250101 (2006)Google Scholar
  7. 7.
    Khatib, O.: Advanced Robotic Manipulation. Stanford University, Stanford, USA, Class Notes (2004)Google Scholar
  8. 8.
    Khatib, O.: A unified approach for motion and force control of robot manipulators: The operational space formulation. International Journal of Robotics Research 3(1), 43–53 (1987)Google Scholar
  9. 9.
    Sentis. Synthesis and Control of Whole-Body Behaviors in Humanoid Systems. PhD thesis, Stanford University, Stanford, USA (2007)Google Scholar
  10. 10.
    Park, J.: Control Strategies For Robot. In: Contact. PhD thesis, Stanford University, Stanford, USA (2006)Google Scholar
  11. 11.
    Chang, K.C., Khatib, O.: Operational space dynamics: Efficient algorithms for modeling and control of branching mechanisms. In: Proceedings of the IEEE International Conference on Robotics and Automation (April 2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Oussama Khatib
    • 1
  • Luis Sentis
    • 1
  • Jae-Heung Park
    • 1
  1. 1.Computer Science DepartmentStanford UniversityStanfordUSA

Personalised recommendations