A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation

arXiv:2404.05858v1 Announce Type: cross
Abstract: Neuromorphic computing mimics computational principles of the brain in $\textit{silico}$ and motivates research into event-based vision and spiking neural networks (SNNs). Event cameras (ECs) exclusively capture local intensity changes and offer superior power consumption, response latencies, and dynamic ranges. SNNs replicate biological neuronal dynamics and have demonstrated potential as alternatives to conventional artificial neural networks (ANNs), such as in reducing energy expenditure and inference time in visual classification. Nevertheless, these novel paradigms remain scarcely explored …

abstract arxiv brain cameras computational computing consumption cs.lg cs.ne cs.ro dynamic dynamics ecs event intensity manipulation networks neural networks neuromorphic neuromorphic computing power power consumption replicate research robot robot manipulation spiking neural networks type vision