Multi-Mode 2D/3D Image Sensor Chip for Next-Generation Intelligent Machine Vision

Information extracted from 2-dimensional (2D) images and 3-dimensional (3D) point clouds drives advancements and transformative changes across many facets of society, from security, manufacturing automation, farming, transportation, urban planning, etc. However, traditional imagers only support 2D image acquisition, which, when used to reconstruct the lost 3D depth information, is feasible but usually slow and inaccurate. This project aims to develop a single-chip CMOS image sensor to achieve 2D and 3D imaging with an efficient laser driver for intelligent machine vision applications. This project proposes four specific technological innovations to contribute to the existing CIS and direct time-of-flight (dToF) research community, including compact pixel design, ADC/TDC readout, VCSEL driver, and an anti-interference modulation scheme.

Hamad Bin Khalifa University (HBKU)