SNN4Agents: A Framework for Developing Energy-Efficient Embodied Spiking Neural Networks for Autonomous Agents

arXiv:2404.09331v1 Announce Type: cross
Abstract: Recent trends have shown that autonomous agents, such as Autonomous Ground Vehicles (AGVs), Unmanned Aerial Vehicles (UAVs), and mobile robots, effectively improve human productivity in solving diverse tasks. However, since these agents are typically powered by portable batteries, they require extremely low power/energy consumption to operate in a long lifespan. To solve this challenge, neuromorphic computing has emerged as a promising solution, where bio-inspired Spiking Neural Networks (SNNs) use spikes from event-based cameras or data …

abstract aerial agents arxiv autonomous autonomous agents batteries cs.ai cs.lg cs.ne cs.ro diverse embodied energy framework however human low mobile networks neural networks productivity robots spiking neural networks tasks trends type unmanned aerial vehicles vehicles