Neuron‐Inspired Time‐of‐Flight Sensing via Spike‐Timing‐Dependent Plasticity of Artificial Synapses. (5th November 2021)

• Record Type: Journal Article
• Authors: Park, Minseong; Yuan, Yuan; Baek, Yongmin; Jones, Andrew H.; Lin, Nicholas; Lee, Doeon; Lee, Hee Sung; Kim, Sihwan; Campbell, Joe C.; Lee, Kyusang
• Is Part Of: Advanced intelligent systems. Volume 4:Number 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-11-05
• Subjects: intelligent matters -- LiDAR -- memristors -- neuromorphic computing -- resistive time-of-flight; Artificial intelligence -- Periodicals; Robotics -- Periodicals; Control theory -- Periodicals; 006.3
• DOI: 10.1002/aisy.202100159
• Languages: English
• ISSNs: 2640-4567

Abstract

Abstract : 3D sensing is a primitive function that allows imaging with depth information generally achieved via the time‐of‐flight (ToF) principle. However, time‐to‐digital converters (TDCs) in conventional ToF sensors are usually bulky, complex, and exhibit large delay and power loss. To overcome these issues, a resistive time‐of‐flight (R‐ToF) sensor that can measure the depth information in an analog domain by mimicking the biological process of spike‐timing‐dependent plasticity (STDP) is proposed herein. The R‐ToF sensors based on integrated avalanche photodiodes (APDs) with memristive intelligent matters achieve a scan depth of up to 55 cm (≈89% accuracy and 2.93 cm standard deviation) and low power consumption (0.5 nJ/step) without TDCs. The in‐depth computing is realized via R‐ToF 3D imaging and memristive classification. This R‐ToF system opens a new pathway for miniaturized and energy‐efficient neuromorphic vision engineering that can be harnessed in light‐detection and ranging (LiDAR), automotive vehicles, biomedical in vivo imaging, and augmented/virtual reality. Abstract : Depth information is achieved by a neuron‐like behavior of memristive intelligent matter. The HfO2 memristors exhibit in‐memory depth sensing capability that can replace the conventional complex memory and time‐to‐digital converter (TDC) logics. By using the proposed resistive time‐of‐flight principle, the 3D imaging capability as well as crossbar‐based image reconstruction and classification are demonstrated.