#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
#
r"""
Overview
--------
This scenario only performs the orbit determination component of the FSW stack.
It uses Hough Cirlces for image processing.
More details can be found in Chapter 4 of `Thibaud Teil's PhD thesis <http://hanspeterschaub.info/Papers/grads/ThibaudTeil.pdf>`_.
The script can be run at full length by calling::
python3 scenario_OpNavOD.py
"""
# Import utilities
from Basilisk.utilities import orbitalMotion, macros, unitTestSupport
from Basilisk.utilities import RigidBodyKinematics as rbk
# Get current file path
import sys, os, inspect, time, signal, subprocess
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, BSKScenario
import BSK_OpNavDynamics, BSK_OpNavFsw
import numpy as np
from sys import platform
# Import plotting file for your scenario
sys.path.append(path + '/../plotting')
import OpNav_Plotting as BSK_plt
# Create your own scenario child class
[docs]class scenario_OpNav(BSKScenario):
"""Main Simulation Class"""
def __init__(self, masterSim):
super(scenario_OpNav, self).__init__(masterSim)
self.name = 'scenario_opnav'
self.masterSim = masterSim
self.filterUse = "bias" #"relOD"
[docs] def log_outputs(self):
print('%s: log_outputs' % self.name)
# Dynamics process outputs: log messages below if desired.
# FSW process outputs
samplingTime = self.masterSim.get_FswModel().processTasksTimeStep
# self.masterSim.TotalSim.logThisMessage(self.masterSim.get_FswModel().trackingErrorCamData.outputDataName, samplingTime)
# self.masterSim.TotalSim.logThisMessage(self.masterSim.get_FswModel().trackingErrorData.outputDataName, samplingTime)
if self.filterUse == "relOD":
self.masterSim.TotalSim.logThisMessage(self.masterSim.get_FswModel().relativeODData.filtDataOutMsgName, samplingTime)
self.masterSim.TotalSim.logThisMessage(self.masterSim.get_FswModel().pixelLineData.opNavOutMsgName, samplingTime)
if self.filterUse == "bias":
self.masterSim.TotalSim.logThisMessage(self.masterSim.get_FswModel().pixelLineFilterData.filtDataOutMsgName, samplingTime)
self.masterSim.TotalSim.logThisMessage(self.masterSim.get_DynModel().scObject.scStateOutMsgName,samplingTime)
self.masterSim.TotalSim.logThisMessage(self.masterSim.get_FswModel().imageProcessing.opnavCirclesOutMsgName, samplingTime)
return
[docs] def pull_outputs(self, showPlots):
print('%s: pull_outputs' % self.name)
# Dynamics process outputs: pull log messages below if any
## Spacecraft true states
position_N = self.masterSim.pullMessageLogData(
self.masterSim.get_DynModel().scObject.scStateOutMsgName + ".r_BN_N", range(3))
velocity_N = self.masterSim.pullMessageLogData(
self.masterSim.get_DynModel().scObject.scStateOutMsgName + ".v_BN_N", range(3))
## Attitude
sigma_BN = self.masterSim.pullMessageLogData(
self.masterSim.get_DynModel().scObject.scStateOutMsgName + ".sigma_BN", range(3))
## Image processing
circleCenters = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().imageProcessing.opnavCirclesOutMsgName+ ".circlesCenters", range(2*10))
circleRadii = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().imageProcessing.opnavCirclesOutMsgName+ ".circlesRadii", range(10))
validCircle = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().imageProcessing.opnavCirclesOutMsgName+ ".valid", range(1))
if self.filterUse == "bias":
NUM_STATES = 9
## Navigation results
navState = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineFilterData.filtDataOutMsgName + ".state", range(NUM_STATES))
navCovar = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineFilterData.filtDataOutMsgName + ".covar",
range(NUM_STATES * NUM_STATES))
navPostFits = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineFilterData.filtDataOutMsgName + ".postFitRes", range(NUM_STATES - 3))
if self.filterUse == "relOD":
NUM_STATES = 6
## Navigation results
navState = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().relativeODData.filtDataOutMsgName + ".state", range(NUM_STATES))
navCovar = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().relativeODData.filtDataOutMsgName + ".covar",
range(NUM_STATES * NUM_STATES))
navPostFits = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().relativeODData.filtDataOutMsgName + ".postFitRes", range(NUM_STATES - 3))
measPos = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineData.opNavOutMsgName + ".r_BN_N", range(3))
r_C = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineData.opNavOutMsgName + ".r_BN_C", range(3))
measCovar = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineData.opNavOutMsgName + ".covar_N", range(3*3))
covar_C = self.masterSim.pullMessageLogData(
self.masterSim.get_FswModel().pixelLineData.opNavOutMsgName + ".covar_C", range(3*3))
sigma_CB = self.masterSim.get_DynModel().cameraMRP_CB
sizeMM = self.masterSim.get_DynModel().cameraSize
sizeOfCam = self.masterSim.get_DynModel().cameraRez
focal = self.masterSim.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:])
pixCovar = np.ones([len(circleCenters[:,0]), 3*3+1])
pixCovar[:,0] = circleCenters[:,0]
pixCovar[:,1:]*=np.array([1,0,0,0,1,0,0,0,2])
if self.filterUse == "relOD":
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(circleCenters[:,0]), 4], np.nan)
trueR_C = np.full([len(circleCenters[:,0]), 4], np.nan)
trueCircles = np.full([len(circleCenters[:,0]), 4], np.nan)
trueCircles[:,0] = circleCenters[:,0]
trueRhat_C[:,0] = circleCenters[:,0]
trueR_C[:,0] = circleCenters[:,0]
centerBias = np.copy(circleCenters)
radBias = np.copy(circleRadii)
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(circleCenters[:,0])):
if circleCenters[i,1:].any() > 1E-8 or circleCenters[i,1:].any() < -1E-8:
if self.filterUse == "bias":
centerBias[i,1:3] = np.round(navState[i, 7:9])
radBias[i,1] = np.round(navState[i, -1])
if self.filterUse == "relOD":
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])
measError_C[i, 1:4] = trueRhat_C[i,1:] - r_C[i, 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]
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:
if self.filterUse == "relOD":
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
if self.filterUse == "relOD":
BSK_plt.plot_TwoOrbits(navState, measPos)
# BSK_plt.AnimatedCircles(sizeOfCam, circleCenters, circleRadii, validCircle)
BSK_plt.diff_vectors(trueR_C, r_C, validCircle, "Circ")
BSK_plt.plot_cirlces(circleCenters, circleRadii, validCircle, sizeOfCam)
BSK_plt.plotStateCovarPlot(stateError, navCovarLong)
if self.filterUse == "bias":
circleCenters[i,1:] += centerBias[i,1:]
circleRadii[i,1:] += radBias[i,1:]
BSK_plt.plotPostFitResiduals(navPostFits, pixCovar)
BSK_plt.imgProcVsExp(trueCircles, circleCenters, circleRadii, np.array(sizeOfCam))
if self.filterUse == "relOD":
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(showPlots, simTime = None):
# Instantiate base simulation
TheBSKSim = BSKSim(fswRate=0.5, dynRate=0.5)
TheBSKSim.set_DynModel(BSK_OpNavDynamics)
TheBSKSim.set_FswModel(BSK_OpNavFsw)
TheBSKSim.initInterfaces()
# Configure a scenario in the base simulation
TheScenario = scenario_OpNav(TheBSKSim)
TheScenario.filterUse = "relOD"
TheScenario.log_outputs()
TheScenario.configure_initial_conditions()
TheBSKSim.get_DynModel().cameraMod.saveImages = 0
# opNavMode 1 is used for viewing the spacecraft as it navigates, opNavMode 2 is for headless camera simulation
TheBSKSim.get_DynModel().vizInterface.opNavMode = 2
mode = ["None", "-directComm", "-opNavMode"]
# The following code spawns the Vizard application from python as a function of the mode selected above, and the platform.
if platform != "darwin":
child = subprocess.Popen([TheBSKSim.vizPath, "--args", mode[TheBSKSim.get_DynModel().vizInterface.opNavMode],
"tcp://localhost:5556"])
else:
child = subprocess.Popen(["open", TheBSKSim.vizPath, "--args", mode[TheBSKSim.get_DynModel().vizInterface.opNavMode],
"tcp://localhost:5556"])
print("Vizard spawned with PID = " + str(child.pid))
# Configure FSW mode
TheScenario.masterSim.modeRequest = 'prepOpNav'
# Initialize simulation
TheBSKSim.InitializeSimulationAndDiscover()
# Configure run time and execute simulation
simulationTime = macros.min2nano(10.)
TheBSKSim.ConfigureStopTime(simulationTime)
print('Starting Execution')
t1 = time.time()
TheBSKSim.ExecuteSimulation()
if TheScenario.filterUse == "relOD":
TheScenario.masterSim.modeRequest = 'OpNavOD'
else:
TheScenario.masterSim.modeRequest = 'OpNavODB'
if simTime != None:
simulationTime = macros.min2nano(simTime)
else:
simulationTime = macros.min2nano(600)
TheBSKSim.ConfigureStopTime(simulationTime)
TheBSKSim.ExecuteSimulation()
t2 = time.time()
print('Finished Execution in ', t2-t1, ' seconds. Post-processing results')
try:
os.kill(child.pid + 1, signal.SIGKILL)
except:
print("IDK how to turn this thing off")
# Pull the results of the base simulation running the chosen scenario
if showPlots:
figureList = TheScenario.pull_outputs(showPlots)
return figureList
else:
return {}
if __name__ == "__main__":
run(True)