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This repository provides Python scripts, lecture materials, and lab exercises for the Robotics and Automation course. It serves as a learning resource for students and researchers exploring robot kinematics, trajectory planning, control strategies, and robotic simulations using Python.

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Robotics and Python Learning

Overview

This repository contains Python scripts, lecture materials, and hands-on exercises for the Robotics and Automation course at Texas A&M International University (TAMIU):

  • CSCE 3345 and SENG 3340 - Robotics and Automation.

It serves as a resource for students learning both robotics concepts and Python programming. The materials are designed to integrate theoretical robotics concepts with practical programming applications using Python and the Robotics Toolbox for Python (by Peter Corke).

Contents

📂 Code Examples

The repository includes well-documented Python scripts covering:

  • Kinematics: Forward and inverse kinematics for robotic manipulators.
  • Trajectory Planning: Path generation and execution.
  • Control Strategies: Basic control approaches for mobile and articulated robots.
  • Simulation: Using Python libraries to model and test robotic behavior.

📂 Lecture Slides

The course slides provide theoretical insights on:

  • Fundamentals of robotics (kinematics, dynamics, and control).
  • Python programming for robotic applications.
  • Simulations using the Robotics Toolbox for Python.

📂 Lab Exercises

Structured lab assignments guide students through:

  • Implementing kinematics and motion planning in Python.
  • Using the Robotics Toolbox for simulations.
  • Writing custom functions to analyze robotic parameters.

Dependencies

To run the scripts in this repository, you will need the following Python libraries:

pip install numpy scipy matplotlib sympy roboticstoolbox

About

This repository provides Python scripts, lecture materials, and lab exercises for the Robotics and Automation course. It serves as a learning resource for students and researchers exploring robot kinematics, trajectory planning, control strategies, and robotic simulations using Python.

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