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New neural tech could power insect-sized intelligent flying robots | The system uses a five-layer spiking neural network with 28,800 neurons to analyze raw event-based camera data and estimate the camera’s 3D motion.
Researchers created a neuromorphic vision-to-control system for autonomous drone flights, utilizing spiking neural networks.
For the project, a Delft University of Technology team in the Netherlands developed a five-layer spiking neural network comprising 28,800 neurons to process raw, event-based camera data. Real-world tests confirmed the pipeline’s performance, demonstrating robustness in various lighting conditions and efficient energy consumption compared to GPU solutions. Specifically, we trained a spiking neural network that accepts raw event-based camera data and outputs low-level control actions for performing autonomous vision-based flight.
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