Re-purposing a modular origami manipulator into an adaptive physical computer for machine learning and robotic perception
Jun Wang, Suyi Li · arXiv · 2025
This study explores using an origami-inspired manipulator as an adaptive physical computer for machine learning and robotic perception.
Plain English summary
Why this matters
Key findings
- The origami manipulator can serve as an adaptive physical reservoir for computing tasks.
- Performance correlates with the Peak Similarity Index (PSI) for time series emulation.
- It can accurately extract payload weight and orientation information.
- Integration of shape memory alloy actuation enhances its computing capabilities.
- The study provides a framework for optimizing design parameters based on task requirements.
What's new
The study systematically evaluates how mechanical design influences physical computing performance in adaptive materials.
Limitations
The abstract does not provide details on the specific configurations tested or the limitations of the proposed framework.
Commercial context
The research is in the early stages of exploring concepts and frameworks without evidence of commercial application.
Publication
- Publisher
- arXiv
- Publication date
- May 5, 2025
- Research type
- Preprint
- arXiv
- 2505.02744
- Access
- open
Tags
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