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Continuous Optical Zoom Compound Eye Imaging Using Alvarez Lenses Actuated by Dielectric Elastomers.
Chuanxun Chen1, Qun Hao1,2, Lin Liu1
1Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing Institute of Technology, Beijing 100081, China.
Biomimetics (Basel, Switzerland)
|June 26, 2024
Summary
A novel continuous optical zoom compound eye imaging system utilizes Alvarez lenses and dielectric elastomers for seamless magnification adjustment. This bio-inspired system offers high resolution and potential for diverse imaging applications.
Area of Science:
- Optics and Photonics
- Biomimetic Engineering
- Materials Science
Background:
- Compound eyes, inspired by nature, offer multi-aperture imaging advantages.
- Traditional zoom systems often rely on bulky mechanical components.
- Alvarez lenses provide tunable focal lengths for optical systems.
Purpose of the Study:
- To propose and demonstrate a continuous optical zoom compound eye imaging system.
- To integrate Alvarez lenses with dielectric elastomers for zoom functionality.
- To achieve zoom without mechanical movement along the optical axis.
Main Methods:
- Designed a system using a curved Alvarez lens array (CALA) and two Alvarez lenses.
- Employed dielectric elastomers (DEs) for actuating lens movement perpendicular to the optical axis.
- Adjusted focal lengths of CALA and Alvarez lenses to achieve continuous zoom.
Main Results:
- Achieved continuous zoom imaging with paraxial magnification ranging from approximately 0.30× to 0.9×.
- Demonstrated a compact optical imaging part with dimensions of 54 mm × 36 mm ×60 mm.
- Obtained an imaging resolution of up to 50 line pairs/mm during optical zoom with a response time of 180 ms.
Conclusions:
- The proposed compound eye imaging system enables continuous optical zoom without axial mechanical movement.
- The system's compact design, rapid response, and high resolution make it suitable for various applications.
- Potential applications include large field of view imaging, medical diagnostics, machine vision, and distance detection.

