Abstract
Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP).1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.
Highlights
Developing neuro-inspired computing paradigms that mimic nervous system functions is a well-established field of research that fosters our understanding of the human brain
NEST is supported through the use of the PyNN abstraction layer (Davison et al, 2008) that provides the same interface for different simulators and for neuromorphic processing units, i.e., dedicated hardware for the simulation of spiking neural network (SNN) such as SpiNNaker (Khan et al, 2008), provided by the Neuromorphic Computing Platform
It can be seen that through the use of the decorators Domain Specific Language (DSL) several properties are specified, such as the type of Transfer Function (TF) (Robot to Neuron), the devices toward the brain simulation and the input coming from the robotic simulation
Summary
Developing neuro-inspired computing paradigms that mimic nervous system functions is a well-established field of research that fosters our understanding of the human brain. While adequate tools exist to simulate either complex neural network models (Gewaltig and Diesmann, 2007) or robots and their environments (Koenig and Howard, 2004), there is so far no tool that allows researchers to connect realistic brain models to a robot and embed it in a sensory-rich environment model Such a tool would require the capability of orchestrating and synchronizing both simulations as well as managing the exchange of data between them. The Neurorobotics Platform (NRP) provides a comprehensive development framework including editors for creating experiments, environments, and brain and robot models These tools are accessible via the web allowing them to use the platform without tedious installation of software packages. One of the pillars of the NRP development is the reuse and extension of existing software, many components were implemented using suitably chosen existing software
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