FPGA-Accelerated Neuromorphic Vision System for Real-Time Orbital Object Detection

2026-06-17 · Diego Hernández, Sebastián Valdivia, Vicente Westerhout, Esteban Vera, Daniel Yunge arxiv

The escalating congestion in orbital space demands advanced monitoring solutions. This work presents a comprehensive open-source framework for neuromorphic resident space object (RSO) detection, adapting the foundational grid clustering algorithm for FPGA acceleration. The system integrates a single event-based camera (EBC) with a custom, distributed processing architecture, where rapid spatial quantization is executed in programmable logic (FPGA) and cluster formation is managed by a software client. We validate this architecture through systematic sampling of night-sky observations from the EVAS dataset, demonstrating 97% detection accuracy for RSOs. The implementation, which serves as a foundational toolkit for event-based FPGA processing, achieves efficient throughput with a total power consumption of 8.5 W and deterministic processing latencies below 62 ms. The architecture's energy efficiency and high-precision detection position it as a viable solution for distributed space surveillance networks.

📄 PDF Abstract BibTeX arXiv:2606.20727

Code (0)

등록된 구현이 없습니다.

Tasks

Object Detection

Hardware-accelerated graph neural networks: an alternative approach for neuromorphic event-based audio classification and keyword spotting on SoC FPGA

2026-02-18 · Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut, Hiroshi Nakano 외 arxiv

As the volume of data recorded by embedded edge sensors increases, particularly from neuromorphic devices producing discrete event streams, there is a growing need for hardware-aware neural architectures that enable effi…

Audio Classification Keyword Spotting

An FPGA Implementation of Convolutional Spiking Neural Networks for Radioisotope Identification

2021-02-24 · Xiaoyu Huang, Edward Jones, Siru Zhang, Shouyu Xie 외

This paper details the FPGA implementation methodology for Convolutional Spiking Neural Networks (CSNN) and applies this methodology to low-power radioisotope identification using high-resolution data. Power consumption …

End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor

2026-05-10 · Wiktor Matykiewicz, Piotr Wzorek, Kamil Jeziorek, Tomás Muñoz 외 arxiv

With the rapid growth of mobile robotics and embedded intelligence, there is an increasing demand for efficient on-device data processing on edge platforms. A promising research direction is the use of neuromorphic senso…

Graph Neural Network Keyword Spotting

Accelerated Feature Detectors for Visual SLAM: A Comparative Study of FPGA vs GPU

2025-10-15 · Ruiqi Ye, Mikel Luján arxiv

Feature detection is a common yet time-consuming module in Simultaneous Localization and Mapping (SLAM) implementations, which are increasingly deployed on power-constrained platforms, such as drones. Graphics Processing…

AceleradorSNN: A Neuromorphic Cognitive System Integrating Spiking Neural Networks and DynamicImage Signal Processing on FPGA

2026-03-30 · Daniel Gutierrez, Ruben Martinez, Leyre Arnedo, Antonio Cuesta 외 arxiv

The demand for high-speed, low-latency, and energy-efficient object detection in autonomous systems -- such as advanced driver-assistance systems (ADAS), unmanned aerial vehicles (UAVs), and Industry 4.0 robotics -- has …