Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid

Alexander Herzog, Nicholas Rotella, Sean Mason, Felix Grimminger, Stefan Schaal, Ludovic Righetti

Research output: Contribution to journalArticle

Abstract

Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.

Original languageEnglish (US)
Pages (from-to)473-491
Number of pages19
JournalAutonomous Robots
Volume40
Issue number3
DOIs
StatePublished - Mar 1 2016

Keywords

  • Force control
  • Hierarchical control
  • Humanoid
  • Inverse dynamics
  • Multi-contact interaction
  • Whole-body control

ASJC Scopus subject areas

  • Artificial Intelligence

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