Event:

Neuromorphic engineering takes inspiration from biology to design brain-like systems that are extremely low-power, fault-tolerant, and capable of adaptation to complex environments. The field of neurorobotics has grown into an exciting area of research and engineering. The common goal is twofold: 1) Developing systems that demonstrate some level of cognitive ability could lead to a better understanding of the neural machinery that realizes cognitive function. 2) Deep theoretical understanding of cognition, neurobiology and behavior obtained by constructing physical systems could lead to a system that demonstrates capabilities commonly found in the animal kingdom, but rarely found in artificial systems. Because of limitations in computation, sensor technology, and robot platforms, combining large-scale neural models with robotics was difficult in the past. In a recent project, we used our GPU accelerated spiking neural network simulator to develop a large-scale model of the visual motion perception pathway in the mammalian cortex. I will present results in which we embody this model on an autonomous mobile robot that leverages smartphone technology. I will discuss the advantages of this approach and how it might lead to future neuromorphic applications.