Optimizing Walking Robot Trajectories
From the series: Modeling, Simulation and Control
Join Sebastian Castro as he outlines a simulation-based workflow for designing and controlling a two-legged walking robot.
In this video, Sebastian shows you how you can leverage MATLAB® and its toolboxes to automate design activities for Simulink® models. Specifically, this demonstration uses the genetic algorithm functionality in Global Optimization Toolbox to find optimal motion trajectories for a walking robot.
Sebastian highlights techniques for setting up optimization inputs and options, running Simulink models from MATLAB to calculate optimization costs, and speeding up repeated simulations.
You can find the example models used in this video on MATLAB Central File Exchange.
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