A Framework for Coupled Simulations of Robots and Spiking Neuronal Networks

Author(s)
Hinkel, Georg and Groenda, Henning and Krach, Sebastian and Vannucci, Lorenzo and Denninger, Oliver and Cauli, Nino and Ulbrich, Stefan and Roennau, Arne and Falotico, Egidio and Gewaltig, Marc-Oliver and Knoll, Alois and Dil
Journal
Journal of Intelligent \& Robotics Systems
Year
2016
Publisher
Springer
Abstract
Bio-inspired robots still rely on classic robot control although advances in neurophysiology allow adaptation to control as well. However, the connection of a robot to spiking neuronal networks needs adjustments for each purpose and requires frequent adaptation during an iterative development. Existing approaches cannot bridge the gap between robotics and neuroscience or do not account for frequent adaptations. The contribution of this paper is an architecture and domain-specific language (DSL) for connecting robots to spiking neuronal networks for iterative testing in simulations, allowing neuroscientists to abstract from implementation details. The framework is implemented in a web-based platform. We validate the applicability of our approach with a case study based on image processing for controlling a four-wheeled robot in an experiment setting inspired by Braitenberg vehicles.
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