On December 23, a collaborative research team composed of Professor Wang Xingjun and Researcher Shu Haowen from Peking University, Professor Wang Cheng's group from City University of Hong Kong, and Professor Zhou Linjie's team from Shanghai Jiao Tong University, published a research paper entitled "Integrated bionic LiDAR for adaptive 4D machine vision" in Nature Communications.

The research team introduced and substantiated a novel architecture for integrated bionic Frequency-Modulated Continuous-Wave (FMCW) LiDAR. Drawing inspiration from the human visual system, this architecture marks the first achievement of an adaptive parallel 4D imaging system with "gazing" capabilities at the chip level.

Through the synergistic operation of a reconfigurable electro-optic frequency comb and a nimble external cavity laser, the system attains ultra-high-resolution adaptive gazing imaging at 0.012°, and facilitates collaborative perception with cameras, thereby enabling 4D+ machine vision expression.

This breakthrough opens up a fresh avenue for next-generation intelligent perception technologies, especially in scenarios like autonomous driving and drones, where there is an urgent need for high resolution, low power consumption, and high flexibility.