Stability Analysis of Legged Locomotion Models by Symmetry-Factored Return Maps

Abstract

We present a new stability analysis for hybrid legged locomotion systems based on the "symmetric" factorization of return maps. We apply this analysis to 2 and 3 degree of freedom (DOF) models of the Spring Loaded Inverted Pendulum (SLIP) with different leg recirculation strategies. Despite the non-integrability of the SLIP dynamics, we obtain a necessary condition for asymptotic stability (and a sufficient condition for instability) at a fixed point, formulated as an exact algebraic expression in the physical parameters. We use this expression to study a variety of 2 DOF SLIP models that have previously been posited as low dimensional representations of running, focusing on the sensory "cost" required to achieve "fast" transients as measured by the degree of singularity of the linearized dynamics. We introduce a new 3 DOF SLIP model with pitching dynamics whose stability properties, revealed by this analysis, provide for the first time the beginnings of a formal explanation for the surprisingly stable gaits of the open loop controlled robot, RHex.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA462040

Entities

People

  • Daniel E. Koditschek
  • Philip Holmes
  • Richard Altendorfer

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Cartesian Coordinates
  • Computer Science
  • Differential Equations
  • Eigenvalues
  • Electrical Engineering
  • Energy
  • Engineering
  • Equations
  • Geometry
  • Hybrid Systems
  • Locomotion
  • Partial Differential Equations
  • Simulations
  • Steady State
  • Symmetry
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Control Systems Engineering.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control