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Walking Robot Pattern Generation

From the series: Modeling, Simulation and Control

Sebastian Castro, MathWorks
Carlos Santacruz-Rosero, MathWorks

Join Sebastian Castro and Carlos Santacruz-Rosero as they discuss the foundations of model-based walking control design for legged humanoid robots. These include the simplified linear inverted pendulum model and the concept of zero-moment point (ZMP).

Sebastian and Carlos demonstrate a few examples of controlling bipedal humanoid robots using zero-moment point manipulation and model predictive control (MPC). In the process, they will also mention some other necessary techniques, such as inverse kinematics and control logic.

You can find the example models used in this video in the MATLAB® Central File Exchange.

  • Understanding Model Predictive Control Video Series
  • Robot Modeling and Simulation: A Walking Robot Case Study

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Watch other Modeling Simulation and Control videos (18 Videos)

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Use MATLAB, Simulink, and Reinforcement Learning Toolbox to train control policies for humanoid robots using deep reinforcement learning.
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Deep Reinforcement Learning for Walking Robots
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