private void timer1_Tick(object sender, EventArgs e) { if (carRunning) { if (timerDiv == 0) { ICarPositionProvider carPos; IFinishPositionProvider finishPos; if (simulation) { itemManager.TakeSample(); carPos = itemManager; finishPos = itemManager; } else { cameraCarPosition.TakeSample(); carPos = cameraCarPosition; finishPos = cameraCarPosition; } //leallitas ha beert a celba double errx = carPos.GetCarState().Position.X - finishPos.GetFinishState(0).Position.X; double erry = carPos.GetCarState().Position.Y - finishPos.GetFinishState(0).Position.Y; double errox = carPos.GetCarState().Orientation.X - finishPos.GetFinishState(0).Orientation.X; double erroy = carPos.GetCarState().Orientation.Y - finishPos.GetFinishState(0).Orientation.Y; if ((errx * errx + erry * erry < CarModel.SHAFT_LENGTH * CarModel.SHAFT_LENGTH) && (errox * errox + erroy * erroy < 0.2)) { buttonStopSim_Click(this, null); } else { carModelGraphicControl1.SetReceiveCommand(); GridCarModelInput oi; GridCarModelState os; neuralController.SimulateOneStep(GridCarModelState.FromCarModelState(carPos.GetCarState()), out oi, out os); outState = GridCarModelState.ToCarModelState(os); outInput = new CarModelInput(oi.Angle); //outInput = new CarModelInput(20, 100); if (checkBoxSerial.Checked) { byte leftspd = (byte)Convert.ToSByte(ComMath.Normal(outInput.LeftSpeed, -180, 180, -128, 127)); byte rightspd = (byte)Convert.ToSByte(ComMath.Normal(outInput.RightSpeed, -180, 180, -128, 127)); //-125, 124 if (checkBoxCarEnable.Checked) { serialComm.Motor_I2C_Forward(1, leftspd, rightspd); } //Thread.Sleep(200); } } } timerDiv = (timerDiv + 1) % (long)(CarModel.SIMULATION_TIME_STEP * 1000.0 / timer1.Interval); if (simulation) { //itemManager.Simulate(new MathModelSimulator(), outInput, timer1.Interval / 1000.0); itemManager.SimualteGrid(new GridMathModelSimulator(), new GridCarModelInput(outInput.LeftSpeed, outInput.RightSpeed), timer1.Interval / 1000.0); } else { cameraCarPosition.Simulate(new MathModelSimulator(), outInput, timer1.Interval / 1000.0); } } carModelGraphicControl1.Invalidate(); }
private static double TrainOneEpoch(MLPDll controller, IGridModelSimulator model, ICarPositionProvider cps, IFinishPositionProvider fps, IObstaclePositionProvider ops, double mu, int maxSimCount, out double SumSimCount, out List <GridCarModelState> innerStates) { double sumSimCount = 0; double error = 0; innerStates = new List <GridCarModelState>(); List <double> deltaws = new List <double>(); MLPDll[] controllers = new MLPDll[maxSimCount]; IGridModelSimulator[] models = new IGridModelSimulator[maxSimCount]; GridCarModelState state = GridCarModelState.FromCarModelState(cps.GetCarState()); GridCarModelInput input = new GridCarModelInput(); //kimenet kiszamitasa int simCount = 0; List <double[]> singleErrors = new List <double[]>(); List <double[]> regularizationErrors = new List <double[]>(); GridCarModelState laststate; bool earlyStop; do { if (simCount == 0) { controllers[simCount] = new MLPDll(controller); //lemasoljuk } else { controllers[simCount] = new MLPDll(controllers[simCount - 1]); } models[simCount] = model.Clone();//a modellt is laststate = state; GridNeuralController.SimulateOneStep(controllers[simCount], models[simCount], state, out input, out state);//vegigszimulaljuk a simCount darab controlleren es modellen innerStates.Add(state); //kozbulso hibak kiszamitasa, itt csak az akadalyoktol valo tavolsag "hibajat" vesszuk figyelembe, irany nem szamit -> hibaja 0 regularizationErrors.Add(obstacleFieldErrorGradient(ops, state, simCount)); //minden pont celtol vett tavolsaga double disterror = ComMath.Normal(state.TargetDist, GridCarModelState.MIN_DIST, GridCarModelState.MAX_DIST, 0, 1); double orientationerror = disterror; if (orientationerror < 0.2) { orientationerror = 0; } double finishorientationerror = disterror; if (finishorientationerror > 0.05) { finishorientationerror = 0; } else { finishorientationerror = 1; } double finishX = Math.Cos(Math.PI - fps.GetFinishState(simCount).Angle); double finishY = Math.Sin(Math.PI - fps.GetFinishState(simCount).Angle); singleErrors.Add(new double[] { -disterror * MAX_NEURON_VALUE, orientationerror * ComMath.Normal(1 - state.TargetOrientation.X, GridCarModelState.MIN_OR_XY, GridCarModelState.MAX_OR_XY, MIN_NEURON_VALUE, MAX_NEURON_VALUE), orientationerror * ComMath.Normal(0 - state.TargetOrientation.Y, GridCarModelState.MIN_OR_XY, GridCarModelState.MAX_OR_XY, MIN_NEURON_VALUE, MAX_NEURON_VALUE), finishorientationerror * ComMath.Normal(finishX - state.TargetFinishOrientation.X, GridCarModelState.MIN_OR_XY, GridCarModelState.MAX_OR_XY, MIN_NEURON_VALUE, MAX_NEURON_VALUE), finishorientationerror * ComMath.Normal(finishY - state.TargetFinishOrientation.Y, GridCarModelState.MIN_OR_XY, GridCarModelState.MAX_OR_XY, MIN_NEURON_VALUE, MAX_NEURON_VALUE) } ); ++simCount; earlyStop = false; if (simCount > 3) { double[] err1 = singleErrors[simCount - 1]; double[] err2 = singleErrors[simCount - 2]; double[] err3 = singleErrors[simCount - 3]; double error1, error2, error3; error1 = error2 = error3 = 0; for (int i = 0; i < 1; i++)//err1.Length { error1 += err1[i] * err1[i]; error2 += err2[i] * err2[i]; error3 += err3[i] * err3[i]; } earlyStop = ((error1 > error2) && (error3 > error2)); if (earlyStop) { //utolso elemet toroljuk singleErrors.RemoveAt(singleErrors.Count - 1); regularizationErrors.RemoveAt(regularizationErrors.Count - 1); innerStates.RemoveAt(innerStates.Count - 1); --simCount; } } }while ((simCount < maxSimCount) && !earlyStop); double[] errors = singleErrors[singleErrors.Count - 1]; sumSimCount += simCount; //hibavisszaterjesztes for (int i = simCount - 1; i >= 0; --i) { double[] sensitibility; models[i].CalcErrorSensibility(errors, out sensitibility); double[] inputSensitibility; inputSensitibility = new double[1]; inputSensitibility[0] = sensitibility[5]; double[] sensitibility2; controllers[i].SetOutputError(inputSensitibility); controllers[i].Backpropagate(); controllers[i].CalculateDeltaWeights(); sensitibility2 = controllers[i].SensitibilityD(); errors[0] = (sensitibility[0] + sensitibility2[0] + 0.1 * singleErrors[i][0]); errors[1] = (sensitibility[1] + sensitibility2[1] + 0 * singleErrors[i][1]); errors[2] = (sensitibility[2] + sensitibility2[2] + 0 * singleErrors[i][2]); errors[3] = (sensitibility[3] + sensitibility2[3] + singleErrors[i][3]); errors[4] = (sensitibility[4] + sensitibility2[4] + singleErrors[i][4]); //regularizaciobol szarmazo hiba hozzaadasa errors[0] += regularizationErrors[i][0]; errors[1] += regularizationErrors[i][1]; errors[2] += regularizationErrors[i][2]; } controller.ClearDeltaWeights(); //sulymodositasok osszegzese for (int i2 = 0; i2 < simCount; ++i2) { controller.AddDeltaWeights(controllers[i2]); } float maxdw = controller.MaxDeltaWeight(); //if (maxdw < 50) maxdw = 50; controller.ChangeWeights(mu / maxdw); ////sulymodositasok osszegzese //for (int i2 = 0; i2 < simCount; ++i2) //simCount //{ // int count = 0; // for (int i = 1; i < controllers[i2]; ++i) // { // foreach (INeuron n in controllers[i2].mlp[i]) // { // foreach (NeuronInput ni in ((Neuron)n).inputs) // { // if (deltaws.Count <= count) deltaws.Add(ni.deltaw); // else deltaws[count] += ni.deltaw; // ++count; // } // } // } //} ////legnagyobb sulymodositas ertekenek meghatarozasa, majd ezzel normalas //double maxdw = 1; //foreach (double dw in deltaws) //{ // if (Math.Abs(dw) > maxdw) maxdw = Math.Abs(dw); //} //if (maxdw < 50) maxdw = 50; ////sulymodositasok ervenyre juttatasa a controllerben //int count2 = 0; //for (int i = 1; i < controller.mlp.Count; ++i) //{ // foreach (INeuron n in controller.mlp[i]) // { // foreach (NeuronInput ni in ((Neuron)n).inputs) // { // ni.w += mu * deltaws[count2] / maxdw; // ++count2; // } // } //} SumSimCount = sumSimCount; return(error); }