Integrated adaptive coherent LiDAR for 4D bionic vision
Ruixuan Chen, Yichen Wu, Ke Zhang, Chuxin Liu, Yikun Chen, Wencan Li,, Bitao Shen, Zhaoxi Chen, Hanke Feng, Zhangfeng Ge, Yan Zhou, Zihan Tao,, Weihan Xu, Yimeng Wang, Pengfei Cai, Dong Pan, Haowen Shu, Linjie Zhou, Cheng, Wang, Xingjun Wang

TL;DR
This paper introduces a bio-inspired, adaptive FMCW LiDAR system that mimics human vision, achieving high-resolution 4D imaging with dynamic focusing, scalable scanning, and multi-parameter sensing using hybrid integrated photonics.
Contribution
The work presents a novel chip-scale, adaptive LiDAR with dynamic zoom and multi-parameter fusion, surpassing traditional LiDAR resolution and capabilities.
Findings
Achieved 0.012-degree resolution, 15 times higher than conventional LiDAR.
Demonstrated 4D parallel imaging with 115 scanning lines.
Enabled high-resolution color-enhanced machine vision through sensor fusion.
Abstract
Light detection and ranging (LiDAR) is a ubiquitous tool to provide precise spatial awareness in various perception environments. A bionic LiDAR that can mimic human-like vision by adaptively gazing at selected regions of interest within a broad field of view is crucial to achieve high-resolution imaging in an energy-saving and cost-effective manner. However, current LiDARs based on stacking fixed-wavelength laser arrays and inertial scanning have not been able to achieve the desired dynamic focusing patterns and agile scalability simultaneously. Moreover, the ability to synchronously acquire multi-dimensional physical parameters, including distance, direction, Doppler, and color, through seamless fusion between multiple sensors, still remains elusive in LiDAR. Here, we overcome these limitations and demonstrate a bio-inspired frequency-modulated continuous wave (FMCW) LiDAR system with…
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Taxonomy
TopicsAdvanced Optical Sensing Technologies · Optical Imaging and Spectroscopy Techniques · Optical Coherence Tomography Applications
