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Reduced-Order Models

  • Tomomichi Sugihara
  • Katsu Yamane
Reference work entry

Abstract

This chapter introduces reduced-order models that have been used in various studies of humanoid motion synthesis and control, particularly for balancing and locomotion. The models may be categorized into two groups. The first group derives physically explicit representations of the simplified system based on the centroidal dynamics embedded in the equation of motion. This category includes a number of successful models, which are intuitively easy to understand. The second group applies systematic order reduction techniques to the full-body dynamics. They make it easy to generalize the reduced-order model to different robot poses or tasks.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Adaptive Machine Systems, Graduate School of EngineeringOsaka UniversitySuita/OsakaJapan
  2. 2.Disney ResearchPittsburghUSA

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