  Deploying advanced imaging solutions to robotic and autonomous systems by
mimicking human vision requires simultaneous acquisition of multiple fields of
views, named the peripheral and fovea regions. Low-resolution peripheral field
provides coarse scene exploration to direct the eye to focus to a highly
resolved fovea region for sharp imaging. Among 3D computer vision techniques,
Light Detection and Ranging (LiDAR) is currently considered at the industrial
level for robotic vision. LiDAR is an imaging technique that monitors pulses of
light at optical frequencies to sense the space and to recover
three-dimensional ranging information. Notwithstanding the efforts on LiDAR
integration and optimization, commercially available devices have slow frame
rate and low image resolution, notably limited by the performance of mechanical
or slow solid-state deflection systems. Metasurfaces (MS) are versatile optical
components that can distribute the optical power in desired regions of space.
Here, we report on an advanced LiDAR technology that uses ultrafast low FoV
deflectors cascaded with large area metasurfaces to achieve large FoV and
simultaneous peripheral and central imaging zones. This technology achieves MHz
frame rate for 2D imaging, and up to KHz for 3D imaging, with extremely large
FoV (up to 150{\deg}deg. on both vertical and horizontal scanning axes). The
use of this disruptive LiDAR technology with advanced learning algorithms
offers perspectives to improve further the perception capabilities and
decision-making process of autonomous vehicles and robotic systems.
