public DroneMove(SystemRandomSource rndGenerator, string fromTask) : base(rndGenerator)
{
angleRandomRotation = new float[7] {
2, 10, 20, 30, 40, 50, 60
};
medianThreshold = new float[7] {
70, 70, 70, 70, 70, 70, 70
};
bestThreshold = new float[7] {
170, 170, 170, 170, 170, 170, 170
};
if (fromTask == "Stabilization")
{
rowIndex = 12;
}
else if (fromTask == "Move")
{
rowIndex = 0;
}
this.fromTask = fromTask;
deltaDistribution = new ContinuousUniform(-5, 5, rndGenerator);
shapes = new List <int>()
{
12, 4
};
signal = new UCSignal(shapes[0]);
individualSize = 0;
for (int i = 0; i < shapes.Count - 1; i++)
{
individualSize += (shapes[i] + 1) * shapes[i + 1];
}
}
public void SendUCSignal(UCSignal signal)
{
UCSignal result = signal;
foreach (Drone.Hardware.Component <UCSignal> component in UCSignalBus)
{
result = component.ProcessSignal(result);
}
}
/**
* \brief Simple constructor of the task. Build all the hyper parameters of the model (Genetic algorithm + MLP). Define the shapes of the MLp and the size of an individual for the genetic part.
*/
public DroneStabilizationNoVelocity(SystemRandomSource rndGenerator, string fromTask) : base(rndGenerator)
{
fromTask = "StabilizationNoVelocity";
rowIndex = 0;
shapes = new List <int>()
{
7, 4
};
signal = new UCSignal(shapes[0]);
individualSize = 0;
for (int i = 0; i < shapes.Count - 1; i++)
{
individualSize += (shapes[i] + 1) * shapes[i + 1];
}
}
/**
* \brief Simple constructor of the task. Build all the hyper parameters of the model (Genetic algorithm + MLP). Define the shapes of the MLp and the size of an individual for the genetic part.
*/
public DroneStabilization(SystemRandomSource rndGenerator, string fromTask) : base(rndGenerator)
{
float mean = 0.0f;
float stdDev = 1.0f;
float deltaT = 0.02f;
noise = new NoiseSensor(mean, stdDev, stdDev, deltaT, rndGenerator);
lowNoise = new NoiseSensor(mean, stdDev/5.0f, stdDev/5.0f, deltaT, rndGenerator);
this.fromTask = "Stabilization";
//Debug.Log(this.fromTask);
rowIndex = 0;
shapes = new List<int>() {9, 4};
signal = new UCSignal(shapes[0]);
individualSize = 0;
for (int i = 0; i < shapes.Count - 1; i++)
{
individualSize += (shapes[i] + 1) * shapes[i + 1];
}
}
