Integrated bionic LiDAR for adaptive 4D machine vision

The human eye achieves high resolution and energy efficiency through adaptive focusing on pertinent details. This natural capability sets a benchmark that current machine vision systems struggle to emulate due to rigid parallel-sensing mechanisms. Efforts to achieve retinal-level resolution through brute-force scaling of channels can lead to prohibitive cost, complexity, and power consumption. Here, we address this bottleneck with a retina-inspired chip-scale LiDAR architecture featuring dynamic gazing capability. By synergizing an agile external cavity laser with reconfigurable electro-optic frequency combs, our integrated photonic platform enables coherent LiDAR with parallel, reconfigurable channels, allocating sensing resources to critical regions without global oversampling. This hardware-efficient design enables real-time comb-based 4D imaging at 0.012° beyond-retinal resolution and supports 4D-plus imaging through cooperative sensing with a camera. With its beyond-retinal resolution, dynamic gazing capability, and scalable chip-level manufacturability, this technology offers a path toward lightweight, high-performance perception across aerial, terrestrial, and marine autonomous systems.

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Publication Details

Journal
Nature Communications
Published
2025-12-23
DOI
https://doi.org/10.1038/s41467-025-66529-7
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrated bionic LiDAR for adaptive 4D machine vision

Y. Zhou, Zhangfeng Ge, Bitao Shen, Yimeng Wang et al.
Nature Communications
Advanced Optical Sensing Technologies
article

Integrated bionic LiDAR for adaptive 4D machine vision

Y. Zhou, Zhangfeng Ge, Bitao Shen, Yimeng Wang, L. P. Zhou, Hanke Feng, Chuxin Liu, Ke Zhang, Xuguang Zhang, Haowen Shu, Wencan Li, Ruixuan Chen, W N Xu, Yichen Wu, Zhaoxi CHEN, Yikun Chen, Dong Pan, Cheng Wang, Xingjun Wang, Pengfei Cai, Zihan Tao
article en

Abstract

The human eye achieves high resolution and energy efficiency through adaptive focusing on pertinent details. This natural capability sets a benchmark that current machine vision systems struggle to emulate due to rigid parallel-sensing mechanisms. Efforts to achieve retinal-level resolution through brute-force scaling of channels can lead to prohibitive cost, complexity, and power consumption. Here, we address this bottleneck with a retina-inspired chip-scale LiDAR architecture featuring dynamic gazing capability. By synergizing an agile external cavity laser with reconfigurable electro-optic frequency combs, our integrated photonic platform enables coherent LiDAR with parallel, reconfigurable channels, allocating sensing resources to critical regions without global oversampling. This hardware-efficient design enables real-time comb-based 4D imaging at 0.012° beyond-retinal resolution and supports 4D-plus imaging through cooperative sensing with a camera. With its beyond-retinal resolution, dynamic gazing capability, and scalable chip-level manufacturability, this technology offers a path toward lightweight, high-performance perception across aerial, terrestrial, and marine autonomous systems.

Nature CommunicationsVol. 17(1)
King University (US), City University of Hong Kong (HK), Shanghai Jiao Tong University (CN), Peking University (CN), Beijing Jiaotong University (CN)
City University of Hong Kong, Croucher Foundation, National Natural Science Foundation of China, Research Grants Council, University Grants Committee, Hong Kong University of Science and Technology, Peking University, National Postdoctoral Program for Innovative Talents
Affordable and clean energy
Openalex Percentile: Top 32%
Advanced Optical Sensing Technologies
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