def testOrient3Model():
env = Environment()
calibrator = ScaleAndOffsetCalibrator(env, 1000, 1 / 100, 10)
for i in range(3):
imu = Orient3IMU()
cal = calibrator.calibrate(imu)
sim = Simulation(environment=env)
traj = RandomTrajectory()
imu.simulation = sim
imu.trajectory = traj
sim.time = imu.trajectory.startTime
BasicIMUBehaviour(imu, 1 / 256, calibration=cal, initialTime=sim.time)
sim.run(traj.endTime)
t = imu.accelerometer.calibratedMeasurements.timestamps
r = traj.rotation(t)
a = r.rotateFrame(
traj.acceleration(t) - env.gravitationalField(traj.position(t), t))
m = r.rotateFrame(env.magneticField(traj.position(t), t))
w = r.rotateFrame(traj.rotationalVelocity(t))
g = env.gravitationalField.nominalMagnitude
a_within_5g = abs(a) < 5 * g
for i in range(3):
yield assert_array_almost_equal, \
np.array([a[i ,a_within_5g[i]]]), \
np.array([imu.accelerometer.calibratedMeasurements(t)
[i, a_within_5g[i]]]), -2
yield assert_array_almost_equal, m, \
imu.magnetometer.calibratedMeasurements(t), 0
yield assert_array_almost_equal, w, \
imu.gyroscope.calibratedMeasurements(t), 0
def testOrient3Model():
env = Environment()
calibrator = ScaleAndOffsetCalibrator(env, 1000, 1/100, 10)
for i in range(3):
imu = Orient3IMU()
cal = calibrator.calibrate(imu)
sim = Simulation(environment=env)
traj = RandomTrajectory()
imu.simulation = sim
imu.trajectory = traj
sim.time = imu.trajectory.startTime
BasicIMUBehaviour(imu, 1/256, calibration=cal, initialTime=sim.time)
sim.run(traj.endTime)
t = imu.accelerometer.calibratedMeasurements.timestamps
r = traj.rotation(t)
a = r.rotateFrame(traj.acceleration(t) -
env.gravitationalField(traj.position(t), t))
m = r.rotateFrame(env.magneticField(traj.position(t), t))
w = r.rotateFrame(traj.rotationalVelocity(t))
g = env.gravitationalField.nominalMagnitude
a_within_5g = abs(a) < 5*g
for i in range(3):
yield assert_array_almost_equal, \
np.array([a[i ,a_within_5g[i]]]), \
np.array([imu.accelerometer.calibratedMeasurements(t)
[i, a_within_5g[i]]]), -2
yield assert_array_almost_equal, m, \
imu.magnetometer.calibratedMeasurements(t), 0
yield assert_array_almost_equal, w, \
imu.gyroscope.calibratedMeasurements(t), 0
def checkSystemSimulation(filterClass):
sim = Simulation()
env = sim.environment
samplingPeriod = 1.0 / 100
calibrator = ScaleAndOffsetCalibrator(env, 1000, samplingPeriod, 20)
simModel = SplinedBodyModel(loadBVHFile(testMotion, conversionFactor=0.01))
sim.time = simModel.startTime
slotTime = 0.001
schedule = Schedule(slotTime, slotTime, range(len(list(simModel.joints))))
def setupIMU(id, joint):
platform = MagicIMU()
calibration = calibrator.calibrate(platform)
platform.simulation = sim
platform.trajectory = joint
filter = filterClass(
initialRotation=joint.rotation(simModel.startTime),
initialTime=sim.time,
initialRotationalVelocity=joint.rotation(
simModel.startTime).rotateFrame(
joint.rotationalVelocity(simModel.startTime)),
gravFieldReference=env.gravitationalField.nominalValue,
magFieldReference=env.magneticField.nominalValue,
**filterParameters.get(filterClass, {}))
def handleSample(behaviour):
rotation = filter.rotation.latestValue
packet = DataPacket(id, [('rotation', rotation)])
behaviour.mac.queuePacket(packet)
behaviour = BasicIMUBehaviour(platform,
samplingPeriod,
calibration,
filter,
handleSample,
initialTime=sim.time)
behaviour.mac = SlaveMAC(platform.radio, behaviour.timerMux, schedule,
id)
return behaviour
imus = [setupIMU(i, joint) for i, joint in enumerate(simModel.joints)]
basestation = IdealBasestation(sim, StaticTrajectory())
recModel = SampledBodyModel.structureCopy(simModel)
reconstructor = BodyModelReconstructor(recModel, initialTime=sim.time)
def handleFrame(packets):
for packet in packets:
packet['jointName'] = recModel.jointNames[packet.source]
reconstructor.handleData(packets, schedule.framePeriod)
MasterMAC(basestation.radio, TimerMultiplexer(basestation.timer), schedule,
handleFrame)
sim.run(simModel.endTime)
for simJoint, recJoint in zip(simModel.joints, recModel.joints):
times = simJoint.rotationKeyFrames.timestamps
assert_quaternions_correlated(simJoint.rotation(times),
recJoint.rotation(times), 0.9)
def checkSystemSimulation(filterClass):
sim = Simulation()
env = sim.environment
samplingPeriod = 1.0/100
calibrator = ScaleAndOffsetCalibrator(env, 1000, samplingPeriod, 20)
simModel = SplinedBodyModel(loadBVHFile(testMotion, conversionFactor=0.01))
sim.time = simModel.startTime
slotTime = 0.001
schedule = Schedule(slotTime, slotTime, range(len(list(simModel.joints))))
def setupIMU(id, joint):
platform = MagicIMU()
calibration = calibrator.calibrate(platform)
platform.simulation = sim
platform.trajectory = joint
filter = filterClass(initialRotation=joint.rotation(simModel.startTime),
initialTime=sim.time,
initialRotationalVelocity=joint.rotation(simModel.startTime)
.rotateFrame(joint.rotationalVelocity(simModel.startTime)),
gravFieldReference=env.gravitationalField.nominalValue,
magFieldReference=env.magneticField.nominalValue,
**filterParameters.get(filterClass, {}))
def handleSample(behaviour):
rotation = filter.rotation.latestValue
packet = DataPacket(id, [('rotation', rotation)])
behaviour.mac.queuePacket(packet)
behaviour = BasicIMUBehaviour(platform, samplingPeriod, calibration,
filter, handleSample, initialTime=sim.time)
behaviour.mac = SlaveMAC(platform.radio, behaviour.timerMux,
schedule, id)
return behaviour
imus = [setupIMU(i, joint) for i, joint in enumerate(simModel.joints)]
basestation = IdealBasestation(sim, StaticTrajectory())
recModel = SampledBodyModel.structureCopy(simModel)
reconstructor = BodyModelReconstructor(recModel, initialTime=sim.time)
def handleFrame(packets):
for packet in packets:
packet['jointName'] = recModel.jointNames[packet.source]
reconstructor.handleData(packets, schedule.framePeriod)
MasterMAC(basestation.radio, TimerMultiplexer(basestation.timer),
schedule, handleFrame)
sim.run(simModel.endTime)
for simJoint, recJoint in zip(simModel.joints, recModel.joints):
times = simJoint.rotationKeyFrames.timestamps
assert_quaternions_correlated(simJoint.rotation(times),
recJoint.rotation(times), 0.9)
def calibrate(self, imu):
calibration = {}
position = vectors.vector(0, 0, 0)
expected = {}
measured = {}
for sensor in imu.sensors:
expected[sensor] = []
measured[sensor] = []
for trajectory in self.testTrajectories():
sim = Simulation(environment=self.environment)
sim.time = 0
imu.simulation = sim
imu.trajectory = trajectory
BasicIMUBehaviour(imu, self.samplingPeriod)
sim.run(self.samplingPeriod * self.samples, printProgress=False)
t = sensor.rawMeasurements.timestamps
for sensor in imu.sensors:
expected[sensor].append(sensor.trueValues(t))
measured[sensor].append(sensor.rawMeasurements.values)
for sensor in imu.sensors:
calibration[sensor] = ScaleAndOffsetCalibration.fromMeasurements(
np.hstack(expected[sensor]), np.hstack(measured[sensor]))
return calibration
def calibrate(self, imu):
calibration = {}
position = vectors.vector(0,0,0)
expected = {}
measured = {}
for sensor in imu.sensors:
expected[sensor] = []
measured[sensor] = []
for trajectory in self.testTrajectories():
sim = Simulation(environment=self.environment)
sim.time = 0
imu.simulation = sim
imu.trajectory = trajectory
BasicIMUBehaviour(imu, self.samplingPeriod)
sim.run(self.samplingPeriod * self.samples,
printProgress=False)
t = sensor.rawMeasurements.timestamps
for sensor in imu.sensors:
expected[sensor].append(sensor.trueValues(t))
measured[sensor].append(sensor.rawMeasurements.values)
for sensor in imu.sensors:
calibration[sensor] = ScaleAndOffsetCalibration.fromMeasurements(
np.hstack(expected[sensor]), np.hstack(measured[sensor]))
return calibration
def testDistLinAccSimulation():
sim = Simulation()
samplingPeriod = 1.0 / 100
calibrator = ScaleAndOffsetCalibrator(sim.environment, 1000, samplingPeriod, 20)
bvhFile = path.join(path.dirname(__file__), "walk.bvh")
sampledModel = loadBVHFile(bvhFile, conversionFactor=0.01)
posTimes = sampledModel.positionKeyFrames.timestamps
sampledModel.positionKeyFrames = TimeSeries(posTimes, np.zeros((3, len(posTimes))))
simModel = SplinedBodyModel(sampledModel)
joints = list(simModel.joints)
sim.time = simModel.startTime
k = 128
slotTime = 0.001
txSlots = range(2, len(joints)) + [0, 1]
auxRxSlots = range(1, len(joints))
auxTxSlots = [joints.index(j.parent) for j in joints[1:]]
schedule = InterSlaveSchedule(slotTime, slotTime, txSlots, auxTxSlots, auxRxSlots)
def setupIMU(id, joint):
offset = randomPosition((-0.1, 0.1))
platform = IdealIMU()
calibration = calibrator.calibrate(platform)
platform.simulation = sim
platform.trajectory = OffsetTrajectory(joint, offset)
filter = DistLinAccelCF(samplingPeriod, platform.trajectory.rotation(simModel.startTime), k, joint, offset)
def updateChildren():
for child in filter.children:
childID = joints.index(child)
childAccel = filter.childAcceleration(child.positionOffset, samplingPeriod)
if childAccel is not None:
auxPacket = AuxPacket(id, childID, [("linearAcceleration", childAccel)])
mac.queueAuxPacket(auxPacket)
def handlePacket(packet):
filter.handleLinearAcceleration(packet["linearAcceleration"], samplingPeriod)
updateChildren()
def handleSample(behaviour):
rotation = filter.rotation.latestValue
packet = DataPacket(id, [("rotation", rotation)])
mac.queuePacket(packet)
if not filter.joint.hasParent:
updateChildren()
behaviour = BasicIMUBehaviour(platform, samplingPeriod, calibration, filter, handleSample, initialTime=sim.time)
mac = InterSlaveMAC(platform.radio, behaviour.timerMux, schedule, id, handlePacket)
imus = [setupIMU(i, joint) for i, joint in enumerate(joints)]
basestation = IdealBasestation(sim, StaticTrajectory())
recModel = SampledBodyModel.structureCopy(simModel)
reconstructor = BodyModelReconstructor(recModel, initialTime=sim.time)
def handleFrame(packets):
for packet in packets:
packet["jointName"] = recModel.jointNames[packet.source]
reconstructor.handleData(packets, schedule.framePeriod)
basestation.radio.channel = schedule.dataChannel
MasterMAC(basestation.radio, TimerMultiplexer(basestation.timer), schedule, handleFrame)
sim.run(simModel.endTime)
for simJoint, recJoint in zip(joints, recModel.joints):
times = simJoint.rotationKeyFrames.timestamps
assert_quaternions_correlated(simJoint.rotation(times), recJoint.rotation(times), 0.85)
def testAgainstReality():
dir = path.dirname(__file__)
filebase = path.join(dir, "swing")
refbase = path.join(dir, "stand")
magbases = [path.join(dir, f) for f in ['magsweep1', 'magsweep2']]
maglookup = {'Upper Leg IMU': '66', 'Orient 8': '8', 'Orient 43': '43'}
magSamples = 2000
refTime = 1.0
posStdDev = 0.0005
rotStdDev = 0.004
ref3D = SplinedMarkerCapture(loadQualisysTSVFile(refbase + "_3D.tsv"),
positionStdDev=posStdDev)
ref6D = SplinedMarkerCapture(loadQualisysTSVFile(refbase + "_6D.tsv"),
rotationStdDev=rotStdDev)
capture3D = SplinedMarkerCapture(loadQualisysTSVFile(filebase + "_3D.tsv"),
positionStdDev=posStdDev)
captureSD = SensorDataCapture.load(filebase + ".sdc")
hip, thigh, knee, shin, ankle = \
['Hip', 'Thigh', 'Knee Hinge', 'Shin', 'Ankle']
jointNames = ['Upper Leg', 'Lower Leg', 'Foot']
jointAbbrevs = ['femur', 'tibia', 'foot']
orientIDs = ['66', '43', '8']
jointMarkerNames = [hip, knee, ankle]
refMarkerNames = [[thigh, knee], [shin, ankle], []]
imuMarkerNames = \
[[j + ' IMU - ' + str(i) for i in range(1,4)] for j in jointNames]
jointMarkerSets = lambda c: [
list(map(c.marker, jointMarkerNames)),
[list(map(c.marker, r)) for r in refMarkerNames],
[list(map(c.marker, i)) for i in imuMarkerNames]
]
imuMarkerSets = lambda c: [[
c.marker(i[0]) for i in imuMarkerNames
], [list(map(c.marker, i[1:])) for i in imuMarkerNames]]
jointRefTrajectories = [
MultiMarkerTrajectory(j, r + i, refTime=refTime)
for j, r, i in zip(*(jointMarkerSets(ref3D)))
]
jointTrajectories = [
MultiMarkerTrajectory(j, r + i, refVectors=m.refVectors) \
for j, r, i, m in \
zip(*(jointMarkerSets(capture3D) + [jointRefTrajectories]))]
imuRefTrajectories = [
MultiMarkerTrajectory(p, r, refTime=refTime)
for p, r in zip(*(imuMarkerSets(ref3D)))
]
imuVecTrajectories = [
MultiMarkerTrajectory(p, r, refVectors=m.refVectors)
for p, r, m in zip(*(imuMarkerSets(capture3D) + [imuRefTrajectories]))
]
imuRefMarkers = [ref6D.marker(j + ' IMU') for j in jointNames]
imuOffsets = [
i.position(refTime) - j.position(refTime)
for i, j in zip(imuRefTrajectories, jointRefTrajectories)
]
imuRotations = [
t.rotation(refTime).conjugate * m.rotation(refTime)
for t, m in zip(imuRefTrajectories, imuRefMarkers)
]
imuTrajectories = [
OffsetTrajectory(v, o, r)
for v, o, r in zip(imuVecTrajectories, imuOffsets, imuRotations)
]
imuData = [captureSD.device(i) for i in orientIDs]
joints = []
for i in range(len(jointNames)):
name = jointNames[i]
traj = jointTrajectories[i]
if i == 0:
model = SampledBodyModel(name)
model.positionKeyFrames = traj.posMarker.positionKeyFrames
joint = model
else:
parent = joints[-1]
refTraj = jointRefTrajectories[i]
parentRefTraj = jointRefTrajectories[i - 1]
pos = refTraj.position(refTime)
parentPos = parentRefTraj.position(refTime)
joint = SampledJoint(joints[-1], name, offset=(pos - parentPos))
joint.rotationKeyFrames = traj.rotationKeyFrames
joints.append(joint)
model = SplinedBodyModel(model)
joints = model.joints
imuJointTrajectories = [
OffsetTrajectory(j, o, r)
for j, o, r in zip(joints, imuOffsets, imuRotations)
]
positionSets = []
valueSets = []
for magbase in magbases:
orient = SensorDataCapture.load(magbase + '.sdc')
optical = loadQualisysTSVFile(magbase + '_6D.tsv')
for marker in optical.markers:
device = orient.device(maglookup[marker.id])
magData = device.sensorData('magnetometer').values
positionSets.append(marker.positionKeyFrames.values)
valueSets.append(
marker.rotationKeyFrames.values.rotateVector(magData))
positions = np.hstack(positionSets)
values = np.hstack(valueSets)
valid = ~np.any(np.isnan(positions), axis=0) & ~np.any(np.isnan(values),
axis=0)
dev = values - np.median(values[:, valid], axis=1).reshape((3, 1))
step = np.shape(values[:, valid])[1] // magSamples
posSamples = positions[:, valid][:, ::step]
valSamples = values[:, valid][:, ::step]
environment = Environment()
environment.magneticField = \
NaturalNeighbourInterpolatedField(posSamples, valSamples)
sim = Simulation(environment=environment)
sim.time = model.startTime
distortIMUs = []
dt = 1 / capture3D.sampled.frameRate
for traj in imuJointTrajectories:
platform = IdealIMU(sim, traj)
distortIMUs.append(BasicIMUBehaviour(platform, dt))
sim.run(model.endTime)
for imu in range(3):
for sensorName in ['accelerometer', 'magnetometer', 'gyroscope']:
sim = getattr(distortIMUs[imu].imu, sensorName).rawMeasurements
true = imuData[imu].sensorData(sensorName)(sim.timestamps +
model.startTime)
yield assert_vectors_correlated, sim.values, true, 0.8
def testDistLinAccSimulation():
sim = Simulation()
samplingPeriod = 1.0/100
calibrator = ScaleAndOffsetCalibrator(sim.environment, 1000,
samplingPeriod, 20)
bvhFile = path.join(path.dirname(__file__), 'walk.bvh')
sampledModel = loadBVHFile(bvhFile, conversionFactor=0.01)
posTimes = sampledModel.positionKeyFrames.timestamps
sampledModel.positionKeyFrames = TimeSeries(
posTimes, np.zeros((3,len(posTimes))))
simModel = SplinedBodyModel(sampledModel)
joints = list(simModel.joints)
sim.time = simModel.startTime
k = 128
slotTime = 0.001
txSlots = list(range(2, len(joints))) + [0,1]
auxRxSlots = range(1, len(joints))
auxTxSlots = [joints.index(j.parent) for j in joints[1:]]
schedule = InterSlaveSchedule(slotTime, slotTime, txSlots,
auxTxSlots, auxRxSlots)
def setupIMU(id, joint):
offset = randomPosition((-0.1, 0.1))
platform = IdealIMU()
calibration = calibrator.calibrate(platform)
platform.simulation = sim
platform.trajectory = OffsetTrajectory(joint, offset)
filter = DistLinAccelCF(samplingPeriod,
platform.trajectory.rotation(simModel.startTime),
k, joint, offset)
def updateChildren():
for child in filter.children:
childID = joints.index(child)
childAccel = filter.childAcceleration(child.positionOffset, samplingPeriod)
if childAccel is not None:
auxPacket = AuxPacket(id, childID,
[('linearAcceleration', childAccel)])
mac.queueAuxPacket(auxPacket)
def handlePacket(packet):
filter.handleLinearAcceleration(packet['linearAcceleration'], samplingPeriod)
updateChildren()
def handleSample(behaviour):
rotation = filter.rotation.latestValue
packet = DataPacket(id, [('rotation', rotation)])
mac.queuePacket(packet)
if not filter.joint.hasParent:
updateChildren()
behaviour = BasicIMUBehaviour(platform, samplingPeriod, calibration,
filter, handleSample, initialTime=sim.time)
mac = InterSlaveMAC(platform.radio, behaviour.timerMux, schedule,
id, handlePacket)
imus = [setupIMU(i, joint) for i, joint in enumerate(joints)]
basestation = IdealBasestation(sim, StaticTrajectory())
recModel = SampledBodyModel.structureCopy(simModel)
reconstructor = BodyModelReconstructor(recModel, initialTime=sim.time)
def handleFrame(packets):
for packet in packets:
packet['jointName'] = recModel.jointNames[packet.source]
reconstructor.handleData(packets, schedule.framePeriod)
basestation.radio.channel = schedule.dataChannel
MasterMAC(basestation.radio, TimerMultiplexer(basestation.timer),
schedule, handleFrame)
sim.run(simModel.endTime)
for simJoint, recJoint in zip(joints, recModel.joints):
times = simJoint.rotationKeyFrames.timestamps
assert_quaternions_correlated(simJoint.rotation(times),
recJoint.rotation(times), 0.85)
trajectory = StaticTrajectory()
#wconst = np.array([0, 1, 0]).reshape(3,1)
#trajectory = StaticContinuousRotationTrajectory(wconst)
imu = MPU9250IMU(simulation=sim, trajectory=trajectory)
GYRO_SAMPLE_RATE = 1000.
dt = 1. / GYRO_SAMPLE_RATE
# Set up a behaviour that runs on the
# simulated IMU
behaviour1 = BasicIMUBehaviour(imu=imu, samplingPeriod=dt)
# Set the time inside the simulation
sim.time = trajectory.startTime
# Run the simulation till the desired
# end time
simulation_length = 3600 * 3
sim.run(simulation_length)
#plt.figure()
#plot(imu.gyroscope.rawMeasurements)
#plt.legend()
#plt.show()
t0 = time.time()
gdata = imu.gyroscope.rawMeasurements.values
savefilename = 'simulated_gyro.npy'
np.save(savefilename, gdata)
save_elapsed = time.time() - t0
print 'Saved {:d} samples to {}. Saving took {:.2f} seconds'.format(
gdata.shape[1], savefilename, save_elapsed)
def testAgainstReality():
dir = path.dirname(__file__)
filebase = path.join(dir, "swing")
refbase = path.join(dir, "stand")
magbases = [path.join(dir, f) for f in ['magsweep1', 'magsweep2']]
maglookup = {
'Upper Leg IMU' : '66',
'Orient 8' : '8',
'Orient 43': '43'}
magSamples = 2000
refTime = 1.0
posStdDev = 0.0005
rotStdDev = 0.004
ref3D = SplinedMarkerCapture(
loadQualisysTSVFile(refbase + "_3D.tsv"), positionStdDev=posStdDev)
ref6D = SplinedMarkerCapture(
loadQualisysTSVFile(refbase + "_6D.tsv"), rotationStdDev=rotStdDev)
capture3D = SplinedMarkerCapture(
loadQualisysTSVFile(filebase + "_3D.tsv"), positionStdDev=posStdDev)
captureSD = SensorDataCapture.load(filebase + ".sdc")
hip, thigh, knee, shin, ankle = \
['Hip', 'Thigh', 'Knee Hinge', 'Shin', 'Ankle']
jointNames = ['Upper Leg', 'Lower Leg', 'Foot']
jointAbbrevs = ['femur', 'tibia', 'foot']
orientIDs = ['66', '43', '8']
jointMarkerNames = [hip, knee, ankle]
refMarkerNames = [[thigh, knee], [shin, ankle], []]
imuMarkerNames = \
[[j + ' IMU - ' + str(i) for i in range(1,4)] for j in jointNames]
jointMarkerSets = lambda c: [
map(c.marker, jointMarkerNames),
[map(c.marker, r) for r in refMarkerNames],
[map(c.marker, i) for i in imuMarkerNames]]
imuMarkerSets = lambda c: [
[c.marker(i[0]) for i in imuMarkerNames],
[map(c.marker,i[1:]) for i in imuMarkerNames]]
jointRefTrajectories = [MultiMarkerTrajectory(j, r + i, refTime=refTime)
for j, r, i in zip(*(jointMarkerSets(ref3D)))]
jointTrajectories = [
MultiMarkerTrajectory(j, r + i, refVectors=m.refVectors) \
for j, r, i, m in \
zip(*(jointMarkerSets(capture3D) + [jointRefTrajectories]))]
imuRefTrajectories = [MultiMarkerTrajectory(p, r, refTime=refTime)
for p, r in zip(*(imuMarkerSets(ref3D)))]
imuVecTrajectories = [MultiMarkerTrajectory(p, r, refVectors=m.refVectors)
for p, r, m in zip(*(imuMarkerSets(capture3D) + [imuRefTrajectories]))]
imuRefMarkers = [ref6D.marker(j + ' IMU') for j in jointNames]
imuOffsets = [i.position(refTime) - j.position(refTime)
for i, j in zip(imuRefTrajectories, jointRefTrajectories)]
imuRotations = [t.rotation(refTime).conjugate * m.rotation(refTime)
for t, m in zip(imuRefTrajectories, imuRefMarkers)]
imuTrajectories = [OffsetTrajectory(v, o, r)
for v, o, r in zip(imuVecTrajectories, imuOffsets, imuRotations)]
imuData = [captureSD.device(i) for i in orientIDs]
joints = []
for i in range(len(jointNames)):
name = jointNames[i]
traj = jointTrajectories[i]
if i == 0:
model = SampledBodyModel(name)
model.positionKeyFrames = traj.posMarker.positionKeyFrames
joint = model
else:
parent = joints[-1]
refTraj = jointRefTrajectories[i]
parentRefTraj = jointRefTrajectories[i - 1]
pos = refTraj.position(refTime)
parentPos = parentRefTraj.position(refTime)
joint = SampledJoint(joints[-1],name, offset=(pos - parentPos))
joint.rotationKeyFrames = traj.rotationKeyFrames
joints.append(joint)
model = SplinedBodyModel(model)
joints = model.joints
imuJointTrajectories = [OffsetTrajectory(j, o, r)
for j, o, r in zip(joints, imuOffsets, imuRotations)]
positionSets = []
valueSets = []
for magbase in magbases:
orient = SensorDataCapture.load(magbase + '.sdc')
optical = loadQualisysTSVFile(magbase + '_6D.tsv')
for marker in optical.markers:
device = orient.device(maglookup[marker.id])
magData = device.sensorData('magnetometer').values
positionSets.append(marker.positionKeyFrames.values)
valueSets.append(
marker.rotationKeyFrames.values.rotateVector(magData))
positions = np.hstack(positionSets)
values = np.hstack(valueSets)
valid = ~np.any(np.isnan(positions),axis=0) & ~np.any(np.isnan(values),axis=0)
dev = values - np.median(values[:,valid],axis=1).reshape((3,1))
step = np.shape(values[:,valid])[1] / magSamples
posSamples = positions[:,valid][:,::step]
valSamples = values[:,valid][:,::step]
environment = Environment()
environment.magneticField = \
NaturalNeighbourInterpolatedField(posSamples, valSamples)
sim = Simulation(environment=environment)
sim.time = model.startTime
distortIMUs = []
dt = 1/capture3D.sampled.frameRate
for traj in imuJointTrajectories:
platform = IdealIMU(sim, traj)
distortIMUs.append(BasicIMUBehaviour(platform, dt))
sim.run(model.endTime)
for imu in range(3):
for sensorName in ['accelerometer', 'magnetometer', 'gyroscope']:
sim = getattr(distortIMUs[imu].imu,sensorName).rawMeasurements
true = imuData[imu].sensorData(sensorName)(sim.timestamps + model.startTime)
yield assert_vectors_correlated, sim.values, true, 0.8
imu = IdealIMU()
imu.simulation = sim
imu.trajectory = joint
def handleSample(behaviour):
pass
behaviour = BasicIMUBehaviour(imu, samplingPeriod, sampleCallback=handleSample, initialTime=sim.time)
return behaviour
joint = simModel.getJoint('rfoot')
#original_quaternions = joint.rotationKeyFrames
behaviour = setupIMU(1, joint)
#show()
sim.run(simModel.endTime)
# get the sensor reading from the IMU at each sample time.
accel = behaviour.imu.accelerometer.rawMeasurements
mag = behaviour.imu.magnetometer.rawMeasurements
gyro = behaviour.imu.gyroscope.rawMeasurements
sample_timestamps = accel.timestamps
accel_values = accel.values
mag_values = mag.values
gyro_values = gyro.values
# Apply the sensor readings to an orientation complimentary filter to compute the orientation of the IMU at each
# sample time
# Set up a behaviour that runs on the
# simulated Camera
behaviour_camera = DefaultCameraBehaviour(camera)
# Set up a behaviour that runs on the
# simulated IMU
dt = 1. / 200
behaviour_imu = BasicIMUBehaviour(imu, dt)
# Set the time inside the simulation
sim.time = trajectory.startTime
# Run the simulation till the desired
# end time
sim.run(trajectory.endTime - camera_model.readout)
PLOT = False
if PLOT:
plt.figure()
plt.subplot(2, 1, 1)
t_camera = behaviour_camera.timestamps
t_imu = imu.gyroscope.rawMeasurements.timestamps
plt.axhline(1, color='k')
plt.axhline(2, color='k')
plt.plot(t_camera, 1 * np.ones_like(t_camera), 'o')
plt.plot(trajectory.startTime + t_imu, 2 * np.ones_like(t_imu), 'x')
plt.ylim(0, 3)
plt.subplot(2, 1, 2)
ts = np.linspace(trajectory.startTime, trajectory.endTime)
plt.plot(ts, trajectory.position(ts).T)