Pose Estimation and Map Formation with Spiking Neural Networks: towards Neuromorphic SLAM

Abstract

In this paper, we investigate the use of ultra low-power, mixed signal analog/digital neuromorphic hardware for implementation of biologically inspired neuronal path integration and map formation for a mobile robot. We perform spiking network simulations of the developed architecture, interfaced to a simulated robotic vehicle. We then port the neuronal map formation architecture on two connected neuromorphic devices, one of which features on-board plasticity, and demonstrate the feasibility of a neuromorphic realization of simultaneous localization and mapping (SLAM).