Integrated bionic LiDAR for adaptive 4D machine vision

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.