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Analysis of the Foot Placement Estimator

Analysis of the Foot Placement Estimator

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Safwan Choudhury

April 14, 2012
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  1. Foot Placement Estimator A Dynamic Measure of Balance for Bipedal

    Robots ECE 688: Course Project Safwan Choudhury
  2. Walking Control Strategies ★ Zero-Moment Point ★ Passive Dynamics ★

    Biologically Inspired Techniques ★ Central Pattern Generators ★ Neural Networks ★ Zero-Hybrid Dynamics
  3. Zero-Moment Point ★ Introduced by Vukobratović in 1968 ★ Point

    where the inertial and gravity moments cancel out (i.e. the moment is zero). ★ Stable if this point is within the support polygon.
  4. 3D Linear Inverted Pendulum ★ Models entire biped as a

    single point mass located at the center of mass (COM)
  5. Remarks on ZMP ★ Popular but energetically inefficient ★ Statically

    stable walking only ★ Very “robotic” (not human-like gait)
  6. Passive Dynamics ★ Introduced by Tad McGeer in 1990 ★

    Powered only by: ★ Force of Gravity ★ Natural Dynamics θ1 θ2 m m mH x z φ
  7. Virtual Passive Dynamics ★ Emulates the force of gravity as

    a small actuator torque θ1 θ2 m m mH x z φ
  8. Remarks on Passive Dynamics ★ Highly energetically efficient ★ Not

    robust (even small perturbations) ★ Very specific initial conditions
  9. Foot Placement Estimator ★ Introduced by Derek Wight in 2008

    ★ Aims to restore balance, instead of constantly maintaining balance.
  10. Remarks on FPE ★ Inherently robust (by design) ★ Can

    combine with simple control strategies ★ Makes a few assumptions (i.e. mass-less legs) ★ Requires fast control + actuators
  11. Contributions to Bipedal Locomotion ★ Can be combined with any

    other approach as an emergency mechanism (even ZMP). ★ Provides an indicator of how unstable the biped is. ★ Biologically verified with human experiments
  12. Project Goals ★ Implement FPE-based control strategy in dynamic simulations

    ★ Constrain sagittal motion without the boom (!)
  13. MASc Goals ★ Virtual Passive Dynamics ★ Foot Placement Estimator

    ★ Minimizing Energy Consumption ★ Human-Like Gait Cycles