Source code for scenario_LimbAttOD

#
#  ISC License
#
#  Copyright (c) 2016, Autonomous Vehicle Systems Lab, University of Colorado at Boulder
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r"""
Overview
--------

This script is called by OpNavScenarios/OpNavMC/MonteCarlo.py in order to make MC data.

"""
# Get current file path
import inspect
import os
import subprocess
import sys

from Basilisk.utilities import RigidBodyKinematics as rbk
# Import utilities
from Basilisk.utilities import orbitalMotion, macros, unitTestSupport

filename = inspect.getframeinfo(inspect.currentframe()).filename
path = os.path.dirname(os.path.abspath(filename))

# Import master classes: simulation base class and scenario base class
sys.path.append(path + '/../..')
from BSK_OpNav import BSKSim
import BSK_OpNavDynamics, BSK_OpNavFsw
import numpy as np

# Import plotting file for your scenario
sys.path.append(path + '/../../plottingOpNav')
import OpNav_Plotting as BSK_plt

# Create your own scenario child class
[docs] class scenario_OpNav(BSKSim): """Main Simulation Class""" def __init__(self): super(scenario_OpNav, self).__init__(BSKSim) self.fswRate = 0.5 self.dynRate = 0.5 self.set_DynModel(BSK_OpNavDynamics) self.set_FswModel(BSK_OpNavFsw) self.name = 'scenario_opnav' self.configure_initial_conditions() self.msgRecList = {} self.retainedMessageNameSc = "scMsg" self.retainedMessageNameFilt = "filtMsg" self.retainedMessageNameOpNav = "opnavMsg" self.retainedMessageNameLimb = "limbMsg" def configure_initial_conditions(self): # Configure Dynamics initial conditions oe = orbitalMotion.ClassicElements() oe.a = 18000 * 1E3 # meters oe.e = 0.6 oe.i = 10 * macros.D2R oe.Omega = 25. * macros.D2R oe.omega = 190. * macros.D2R oe.f = 80. * macros.D2R # 90 good mu = self.get_DynModel().gravFactory.gravBodies['mars barycenter'].mu rN, vN = orbitalMotion.elem2rv(mu, oe) orbitalMotion.rv2elem(mu, rN, vN) bias = [0, 0, -2] rError= np.array([10000.,10000., -10000]) vError= np.array([100, -10, 10]) MRP= [0,-0.3,0] self.get_FswModel().relativeOD.stateInit = (rN+rError).tolist() + (vN+vError).tolist() self.get_DynModel().scObject.hub.r_CN_NInit = rN # m - r_CN_N self.get_DynModel().scObject.hub.v_CN_NInit = vN # m/s - v_CN_N self.get_DynModel().scObject.hub.sigma_BNInit = [[MRP[0]], [MRP[1]], [MRP[2]]] # sigma_BN_B self.get_DynModel().scObject.hub.omega_BN_BInit = [[0.0], [0.0], [0.0]] # rad/s - omega_BN_B qNoiseIn = np.identity(6) qNoiseIn[0:3, 0:3] = qNoiseIn[0:3, 0:3] * 1E-3 * 1E-3 qNoiseIn[3:6, 3:6] = qNoiseIn[3:6, 3:6] * 1E-4 * 1E-4 self.get_FswModel().relativeOD.qNoise = qNoiseIn.reshape(36).tolist() self.get_FswModel().horizonNav.noiseSF = 20 def log_outputs(self): # Dynamics process outputs: log messages below if desired. FswModel = self.get_FswModel() DynModel = self.get_DynModel() # FSW process outputs samplingTime = self.get_FswModel().processTasksTimeStep self.msgRecList[self.retainedMessageNameSc] = DynModel.scObject.scStateOutMsg.recorder(samplingTime) self.AddModelToTask(DynModel.taskName, self.msgRecList[self.retainedMessageNameSc]) self.msgRecList[self.retainedMessageNameFilt] = FswModel.relativeOD.filtDataOutMsg.recorder(samplingTime) self.AddModelToTask(DynModel.taskName, self.msgRecList[self.retainedMessageNameFilt]) self.msgRecList[self.retainedMessageNameOpNav] = FswModel.opnavMsg.recorder(samplingTime) self.AddModelToTask(DynModel.taskName, self.msgRecList[self.retainedMessageNameOpNav]) self.msgRecList[self.retainedMessageNameLimb] = FswModel.limbFinding.opnavLimbOutMsg.recorder(samplingTime) self.AddModelToTask(DynModel.taskName, self.msgRecList[self.retainedMessageNameLimb]) return def pull_outputs(self, showPlots): # Dynamics process outputs: pull log messages below if any ## Spacecraft true states scRec = self.msgRecList[self.retainedMessageNameSc] position_N = unitTestSupport.addTimeColumn(scRec.times(), scRec.r_BN_N) velocity_N = unitTestSupport.addTimeColumn(scRec.times(), scRec.v_BN_N) ## Attitude sigma_BN = unitTestSupport.addTimeColumn(scRec.times(), scRec.sigma_BN) ## Image processing limbRec = self.msgRecList[self.retainedMessageNameLimb] limb = unitTestSupport.addTimeColumn(limbRec.times(), limbRec.limbPoints) numLimbPoints = unitTestSupport.addTimeColumn(limbRec.times(), limbRec.numLimbPoints) validLimb = unitTestSupport.addTimeColumn(limbRec.times(), limbRec.valid) ## OpNav Out opNavRec = self.msgRecList[self.retainedMessageNameOpNav] measPos = unitTestSupport.addTimeColumn(opNavRec.times(), opNavRec.r_BN_N) r_C = unitTestSupport.addTimeColumn(opNavRec.times(), opNavRec.r_BN_C) measCovar = unitTestSupport.addTimeColumn(opNavRec.times(), opNavRec.covar_N) covar_C = unitTestSupport.addTimeColumn(opNavRec.times(), opNavRec.covar_C) NUM_STATES = 6 ## Navigation results filtRec = self.msgRecList[self.retainedMessageNameFilt] navState = unitTestSupport.addTimeColumn(filtRec.times(), filtRec.state) navCovar = unitTestSupport.addTimeColumn(filtRec.times(), filtRec.covar) navPostFits = unitTestSupport.addTimeColumn(filtRec.times(), filtRec.postFitRes) sigma_CB = self.get_DynModel().cameraMRP_CB sizeMM = self.get_DynModel().cameraSize sizeOfCam = self.get_DynModel().cameraRez focal = self.get_DynModel().cameraFocal #in m pixelSize = [] pixelSize.append(sizeMM[0] / sizeOfCam[0]) pixelSize.append(sizeMM[1] / sizeOfCam[1]) dcm_CB = rbk.MRP2C(sigma_CB) # Plot results BSK_plt.clear_all_plots() stateError = np.zeros([len(position_N[:,0]), NUM_STATES+1]) navCovarLong = np.full([len(position_N[:,0]), 1+NUM_STATES*NUM_STATES], np.nan) navCovarLong[:,0] = np.copy(position_N[:,0]) stateError[:, 0:4] = np.copy(position_N) stateError[:,4:7] = np.copy(velocity_N[:,1:]) measError = np.full([len(measPos[:,0]), 4], np.nan) measError[:,0] = measPos[:,0] measError_C = np.full([len(measPos[:,0]), 5], np.nan) measError_C[:,0] = measPos[:,0] trueRhat_C = np.full([len(numLimbPoints[:,0]), 4], np.nan) trueR_C = np.full([len(numLimbPoints[:,0]), 4], np.nan) trueCircles = np.full([len(numLimbPoints[:,0]), 4], np.nan) trueCircles[:,0] = numLimbPoints[:,0] trueRhat_C[:,0] = numLimbPoints[:,0] trueR_C[:,0] = numLimbPoints[:,0] switchIdx = 0 Rmars = 3396.19*1E3 for j in range(len(stateError[:, 0])): if stateError[j, 0] in navState[:, 0]: stateError[j, 1:4] -= navState[j - switchIdx, 1:4] stateError[j, 4:] -= navState[j - switchIdx, 4:] else: stateError[j, 1:] = np.full(NUM_STATES, np.nan) switchIdx += 1 for i in range(len(numLimbPoints[:,0])): if numLimbPoints[i,1] > 1E-8: measError[i, 1:4] = position_N[i +switchIdx, 1:4] - measPos[i, 1:4] measError_C[i, 4] = np.linalg.norm(position_N[i +switchIdx, 1:4]) - np.linalg.norm(r_C[i, 1:4]) trueR_C[i,1:] = np.dot(np.dot(dcm_CB, rbk.MRP2C(sigma_BN[i +switchIdx, 1:4])) , position_N[i +switchIdx, 1:4]) trueRhat_C[i,1:] = np.dot(np.dot(dcm_CB, rbk.MRP2C(sigma_BN[i +switchIdx, 1:4])) ,position_N[i +switchIdx, 1:4])/np.linalg.norm(position_N[i +switchIdx, 1:4]) trueCircles[i,3] = focal*np.tan(np.arcsin(Rmars/np.linalg.norm(position_N[i,1:4])))/pixelSize[0] trueRhat_C[i,1:] *= focal/trueRhat_C[i,3] measError_C[i, 1:4] = trueRhat_C[i,1:] - r_C[i, 1:4]/np.linalg.norm(r_C[i, 1:4]) trueCircles[i, 1] = trueRhat_C[i, 1] / pixelSize[0] + sizeOfCam[0]/2 - 0.5 trueCircles[i, 2] = trueRhat_C[i, 2] / pixelSize[1] + sizeOfCam[1]/2 - 0.5 else: measCovar[i,1:] = np.full(3*3, np.nan) covar_C[i, 1:] = np.full(3 * 3, np.nan) navCovarLong[switchIdx:,:] = np.copy(navCovar) timeData = position_N[:, 0] * macros.NANO2MIN BSK_plt.plot_TwoOrbits(position_N, measPos) BSK_plt.diff_vectors(trueR_C, r_C, validLimb, "Limb") BSK_plt.plot_limb(limb, numLimbPoints, validLimb, sizeOfCam) # BSK_plt.AnimatedScatter(sizeOfCam, circleCenters, circleRadii, validCircle) BSK_plt.plotStateCovarPlot(stateError, navCovarLong) # BSK_plt.imgProcVsExp(trueCircles, circleCenters, circleRadii, np.array(sizeOfCam)) BSK_plt.plotPostFitResiduals(navPostFits, measCovar) figureList = {} if showPlots: BSK_plt.show_all_plots() else: fileName = os.path.basename(os.path.splitext(__file__)[0]) figureNames = ["attitudeErrorNorm", "rwMotorTorque", "rateError", "rwSpeed"] figureList = BSK_plt.save_all_plots(fileName, figureNames) return figureList
def run(TheScenario): TheScenario.log_outputs() TheScenario.configure_initial_conditions() TheScenario.get_FswModel().imageProcessing.saveImages = 0 TheScenario.get_DynModel().vizInterface.opNavMode = 1 mode = ["None", "-directComm", "-noDisplay"] vizard = subprocess.Popen( [TheScenario.vizPath, "--args", mode[TheScenario.get_DynModel().vizInterface.opNavMode], "tcp://localhost:5556"], stdout=subprocess.DEVNULL) print("Vizard spawned with PID = " + str(vizard.pid)) # Configure FSW mode TheScenario.modeRequest = 'prepOpNav' # Initialize simulation TheScenario.InitializeSimulation() # Configure run time and execute simulation simulationTime = macros.min2nano(3.) TheScenario.ConfigureStopTime(simulationTime) TheScenario.ExecuteSimulation() TheScenario.modeRequest = 'OpNavAttODLimb' # TheBSKSim.get_DynModel().SetLocalConfigData(TheBSKSim, 60, True) simulationTime = macros.min2nano(100.) TheScenario.ConfigureStopTime(simulationTime) TheScenario.ExecuteSimulation() vizard.kill() spice = TheScenario.get_DynModel().gravFactory.spiceObject spice.unloadSpiceKernel(spice.SPICEDataPath, 'de430.bsp') spice.unloadSpiceKernel(spice.SPICEDataPath, 'naif0012.tls') spice.unloadSpiceKernel(spice.SPICEDataPath, 'de-403-masses.tpc') spice.unloadSpiceKernel(spice.SPICEDataPath, 'pck00010.tpc') return if __name__ == "__main__": # Instantiate base simulation # Configure a scenario in the base simulation TheScenario = scenario_OpNav() run(TheScenario)