IEEE ENVISION PROJECT: BIPEDAL ROBOT SIMULATION USING MATLAB

The following project uses the Matlab toolkits to configure and simulate the working of a bipedal robot

Introduction

This repository contains example files for the following MATLAB and Simulink Robotics Arena videos on walking robots.

• Basics of walking robots
• Modeling and simulation
• Trajectory optimization
• Walking pattern generation
• Deep reinforcement learning

You can also learn more about this example from our blog posts on modeling and simulation and control.

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Setup

Run startupWalkingRobot.m to get the MATLAB path ready.

Below are the main folders containing various walking robot examples:

1. LIPM -- Shows how to generate a walking pattern using the linear inverted pendulum model (LIPM), which is one of the foundational models for humanoid walking control.

2. ModelingSimulation -- Shows how to build the simulation of the walking robot, including contact forces, various actuator models, and importing from CAD.

3. Optimization -- Shows how to use genetic algorithms to optimize joint angle trajectories for stability and speed.

4. ControlDesign -- Shows how to create closed-loop walking controllers using common techniques like Zero Moment Point (ZMP) manipulation and Model Predictive Control (MPC) for pattern generation.

5. ReinforcementLearning -- Shows how to set up and train a Deep Deterministic Policy Gradient (DDPG) reinforcement learning agent for learning how to walk.

Each of these folders has its own separate README with more information.

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