Merged in NRRPLT-7271-choose-and-view-brain-type (pull request #61)

[NRRPLT-7271] Add default braitenberg Nengo brain model

Approved-by: Ugo Albanese

brains/braitenberg_nengo/braitenberg_nengo.py

+import nengo
+
+circuit = nengo.Network()
+with circuit:
+    # Now we create an Ensembles of 1000 neurons.  These 1000 neurons are
+    # configured to form a distributed representation of three values for
+    # sensation, and two values for actuation (i.e.
+    # each neuron gets an input current that is some random combination
+    # of those three values). The actors population simply redirects the
+    # neurally encoded value to the connected motors of the husky robot.
+    sensors = nengo.Ensemble(n_neurons=1000, dimensions=3)
+    actors = nengo.Ensemble(n_neurons=2, dimensions=2, neuron_type=nengo.Direct())
+
+    # Now we tell Nengo what computation we want the neurons to
+    # approximate.  Nengo will use this to find connection weights
+    # between 'sensors' (the perception ensemble) and 'actors' (the output ensemble)
+    # that will best approximate the function we give it.
+    #
+    # It should be noted that we can do anything we want
+    # here in this function.  We could do some complex algorithm
+    # involving trig functions, multiple branching if statements,
+    # or whatever.  Nengo will attempt to approximate that function
+    # using the neurons.
+    #
+    # The synapse=0.1 parameter indicates that the connections
+    # defined here have a synapse that is an exponential low-pass
+    # filter with a time constant of 100ms.
+    def control(x):
+        rl, rr, gb = x
+        forward = min(1.0, max(-0.01, (min(rl, rr)) * 100000))
+        turn = max(min((rl - rr) * 100, 1), -1)
+        if max(rl, rr) < 0.1:
+            forward = -0.001
+            turn = 0.5
+        return forward, turn
+
+    nengo.Connection(sensors, actors, function=control, synapse=0.1)

brains/braitenberg_nengo/model.config

+<?xml version='1.0'?>
+<model xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://schemas.humanbrainproject.eu/SP10/2017/brain_model_config" xsi:schemaLocation="http://schemas.humanbrainproject.eu/SP10/2017/brain_model_config ../brain_model_configuration.xsd">
+	<name>braitenberg_nengo</name>
+	<version>1.0</version>
+        <maturity>production</maturity>
+	<brain>braitenberg_nengo.py</brain>
+	<sdf version="1.6">model.sdf</sdf>
+	<author>
+		<name>Lazar Mateev</name>
+	</author>
+	<author>
+		<name>Georg Hinkel</name>
+	</author>
+	<description>
+	    This file contains the setup of the neuronal network running the Husky experiment with neuronal image recognition.
+    </description>
+</model>