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Robotics

BRIDGE: An Open-Source Humanoid Platform via Morphology-Control Co-Design for Physical AI

Jianren Wang, Letian Qian, Zikai Wang, Weiwei Wu, Junjie Zong, Abhinav Gupta, Deepak Pathak

Featured September 6, 2026

Original Paper

AI-generated analysis — This is SciGrove's AI interpretation of the paper, not peer-reviewed content. Always refer to the original paper.

Simply

Robots usually have their body designed first and then learn to move, but this paper creates a co-design process where the robot's body and how it moves are designed together, making it much better at mimicking human actions.

In depth
The paper introduces a morphology-control co-design framework that iteratively optimizes humanoid robot hardware and control policies together. This approach aims to overcome the limitations of traditional decoupled design by ensuring the robot's physical form is inherently suited for human-like movements, quantified by a novel human-likeness metric that considers both kinematic fidelity and dynamic tracking performance.

Key Takeaways

  • 1
    A novel morphology-control co-design framework is introduced, optimizing robot hardware and control policies concurrently for human-like movement.
  • 2
    A unified human-likeness metric is proposed, combining kinematic retargeting fidelity and dynamic tracking performance to evaluate robot designs.
  • 3
    The BRIDGE platform, an 88cm open-source humanoid, is developed using this framework, demonstrating superior human motion capture and dynamic capabilities.

Conceptual Flow

HIGH LEVEL
1
Methodology (The 'Logic')

The paper designs robot bodies and their movements together, making sure the body can actually do the movements well.

Human Motion Data
Robot Body Ideas
Co-Design & Test
Best Robot Body
Best Movement Plan
2
Results (The 'Impact')

The new robot design moves more like a human and performs better than other robots, especially for tricky, fast actions.

BRIDGE Robot
Other Robots
Compare Movement
BRIDGE Moves Best
More Human-like

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