Enhancing Zero Moment Point-Based Control Model: System Identification Approach

The approximation of a humanoid robot by an inverted pendulum is one of the most frequently used models to generate a stable walking pattern using a planned zero moment point (ZMP) trajectory. However, on account of the difference between the multibody model of the humanoid robot and the simple inve...

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Bibliographic Details
Published in:Advanced robotics 2011-01, Vol.25 (3-4), p.427-446
Main Authors: Suleiman, Wael, Kanehiro, Fumio, Miura, Kanako, Yoshida, Eiichi
Format: Article
Language:English
Subjects:
Dynamical systems
Dynamics
Humanoid
HUMANOID ROBOT
NONLINEAR SYSTEM CONTROL
OPTIMIZATION
Pattern generation
Pendulums
Robots
SYSTEM IDENTIFICATION
Walking
ZERO MOMENT POINT CONTROL
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Summary:The approximation of a humanoid robot by an inverted pendulum is one of the most frequently used models to generate a stable walking pattern using a planned zero moment point (ZMP) trajectory. However, on account of the difference between the multibody model of the humanoid robot and the simple inverted pendulum model, the ZMP error might be bigger than the polygon of support and the robot falls down. To overcome this limitation, we propose to improve the accuracy of the inverted pendulum model using system identification techniques. The candidate model is a quadratic in the state space representation. To identify this system, we propose an identification method that is the result of the comprehensive application of system identification to dynamic systems. Based on the quadratic system, we also propose controlling algorithms for on-line and off-line walking pattern generation for humanoid robots. The efficiency of the quadratic system and the walking pattern generation methods has been successfully shown using dynamical simulation and conducting real experiments on the cybernetic human HRP-4C.
ISSN:0169-1864
1568-5535
DOI:10.1163/016918610X551773