# MABEL: Open-source 56-DOF bimanual mobile robot released by NYU and University of Toronto

> **Key takeaway:** MABEL is a fully open-source, high-degree-of-freedom mobile manipulator designed for robotics research and teleoperation.

**Published:** 2026-11-06T17:15:11+00:00 
**Source:** ROS Robot Operating System News 
**Category:** robotics-science 
**Canonical URL:** https://fosswire.org/news/mabel-open-source-56-dof-bimanual-mobile-robot-released-by-n.html 

## Summary
Researchers from New York University and the University of Toronto have introduced MABEL, a highly complex bimanual mobile robot featuring 56 degrees of freedom (DOF). The platform is designed to support advanced robotics research, including simulation, learning, and teleoperation using an Apple Vision Pro.

The project is released under a fully open model, utilizing the CERN-OHL-S-2.0 license for hardware and the Apache-2.0 license for software. It provides a comprehensive ecosystem including firmware, ROS 2 integration, and simulation capabilities to facilitate reproducible research in humanoid and mobile manipulation.

## Technical Specifications and Architecture
- **Kinematics and DOF:** The system comprises a three-wheel swerve base, a vertical lift, a pitching torso, and a 3-DOF head equipped with stereo cameras, totaling 56 degrees of freedom.
- **Manipulator Subsystems:** The robot utilizes two 7-DOF arms based on the OpenArm design and two 17-DOF tendon-driven hands derived from the ORCA Hand project.
- **Control and Compute:** The hardware architecture incorporates Teensy 4.1 microcontrollers for low-level control and supports the ROS 2 middleware framework.
- **Licensing and Documentation:** Hardware designs are provided under CERN-OHL-S-2.0, software under Apache-2.0, and all documentation and media are released under CC BY 4.0.

## Why it matters
By providing a high-DOF, open-source alternative to expensive proprietary research platforms, MABEL lowers the barrier to entry for academic and independent developers working on bimanual manipulation and AI-driven robotics. The inclusion of ROS 2 and simulation support ensures compatibility with modern robotics software stacks and machine learning workflows.