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OpenSCAD Humanoid with MuJoCo Controls

Description

This repository contains the design and control code for an open-source humanoid robot. The design of the robot is created using OpenSCAD, a script-based 3D CAD modeler, allowing for parametric and fully customizable design files. The control of the humanoid is managed using Python, interfacing with the MuJoCo (Multi-Joint dynamics with Contact) physics engine, which provides a realistic simulation environment for the robot.

Features

• Parametric Design: The humanoid robot's structure is fully defined in OpenSCAD, enabling users to modify dimensions, joint angles, and other physical properties easily.
• Python Control Scripts: Control algorithms written in Python, allowing users to simulate, test, and refine control strategies for the humanoid's movements.
• MuJoCo Integration: The repository leverages MuJoCo's advanced physics simulation capabilities to create a realistic environment for testing the robot's dynamics and control systems.
• Customizable Components: Users can design and simulate various components, such as arms, legs, and sensors, to suit different research and development needs.
• Simulation Environment: Pre-built environments in MuJoCo for testing walking, balancing, and complex maneuvers.

Getting Started

1. Clone the Repository: Start by cloning the repository to your local machine.
2. OpenSCAD Design: Customize the humanoid design using the provided OpenSCAD files.
3. Python & MuJoCo Setup: Follow the setup instructions to install Python dependencies and configure MuJoCo for your system.
4. Run Simulations: Use the provided Python scripts to simulate the humanoid's behavior in MuJoCo, with various control strategies available.

Prerequisites

• OpenSCAD installed for editing and viewing the 3D models.
• Python 3.x with necessary libraries (e.g., NumPy, MuJoCo Python bindings).
• MuJoCo installed and properly configured with a valid license.

Usage

• Customization: Modify the step_bot.scad file to change the humanoid's design parameters.
• Control Algorithms: Implement and test control algorithms in Python using the provided templates.
• Simulation: Run the simulation scripts to observe the robot's performance under different conditions.

Contributing

Contributions are welcome! Feel free to fork the repository, make your changes, and submit a pull request. Please make sure to document any new features or modifications.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions, suggestions, or contributions, please reach out to aj3944@nyu.edu.

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This repository bridges the gap between mechanical design and control systems, enabling researchers, educators, and enthusiasts to explore humanoid robotics in an open-source and customizable environment.

Stair Traversal and Exploration Project (STEP)

Team STEP at NYU is dedicated to advancing the capabilities of autonomous robots in navigating complex, stair-filled environments. The project focuses on designing and prototyping robotic systems with specialized hardware and control algorithms that enable precise movement on uneven and inclined surfaces. Leveraging sensor fusion techniques, STEP integrates LIDAR, IMUs, and vision systems to enhance real-time environmental perception and decision-making. The ultimate goal is to create robots capable of autonomous exploration and traversal in challenging terrains, with applications in search and rescue, urban exploration, and infrastructure inspection.

As part of NYU's Vertically Integrated Projects (VIP) program, STEP offers students the chance to earn academic credit while contributing to cutting-edge research. Participants from various disciplines collaborate on long-term, multidisciplinary tasks, developing skills in robotics, control systems, and sensor integration. This project not only provides hands-on experience but also positions students to make impactful contributions to the field of autonomous robotics.