Live Demonstration: Low Power and Real-Time Obstacle Avoidance System with CMOS Image Sensor and Spiking Neural Network

This demo showcases a system that can detect obstacles and control a character in the simulator to avoid collisions in real-time. This system consists of the following components: a low-power CMOS image sensor that provides high-resolution images, a lightweight spiking neural network that uses monocular inertial-visual input to sense the depth of obstacles, and a spiking neural network accelerator that speeds up the heavy computation of the neural network. The entire system can run at 25 FPS and demonstrates the capability to avoid obstacles quickly and accurately.

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Publication Details

Published
2024-11-07
DOI
https://doi.org/10.1109/apccas62602.2024.10808551
Primary Topic
CCD and CMOS Imaging Sensors
Type
article
Field-Weighted Citation Impact
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article

Live Demonstration: Low Power and Real-Time Obstacle Avoidance System with CMOS Image Sensor and Spiking Neural Network

Wei‐Chi Huang, Chen-Fu Yeh, Po‐An Chen, Yu-Chih Tsai et al.
CCD and CMOS Imaging Sensors
article

Live Demonstration: Low Power and Real-Time Obstacle Avoidance System with CMOS Image Sensor and Spiking Neural Network

Wei‐Chi Huang, Chen-Fu Yeh, Po‐An Chen, Yu-Chih Tsai, Kea-Tiong Tang
article en

Abstract

This demo showcases a system that can detect obstacles and control a character in the simulator to avoid collisions in real-time. This system consists of the following components: a low-power CMOS image sensor that provides high-resolution images, a lightweight spiking neural network that uses monocular inertial-visual input to sense the depth of obstacles, and a spiking neural network accelerator that speeds up the heavy computation of the neural network. The entire system can run at 25 FPS and demonstrates the capability to avoid obstacles quickly and accurately.

National Tsing Hua University (TW)
Openalex Percentile: Top 78%
CCD and CMOS Imaging Sensors
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