Closing the motor control loop with neuromorphic hardware
We focus on solving an engineering problem of interfacing (i) sensory input (DAVIS camera), (ii) a spiking network on a neuromorphic processor and (iii) a motor output (robotic arm) to build an event-based framework to test some learning schemes (unsupervised STDP and reinforcement learning) that close the perception-action loop.
As a starting spiking building block we will use a threeway relational network that maps the eye-centered stimulus position, the position of the arm and the distance between them in retinal coordinates.
|Wed, 24.04.2019||20:30 - 21:00||Disco|
|Thu, 25.04.2019||20:30 - 21:30||Disco|
|Fri, 26.04.2019||19:00 - 20:00||Disco|