def testVideoGeneration():
samp = loadBVHFile(os.path.join(os.path.dirname(__file__),
'../system/walk.bvh'), 0.01)
spl = SplinedBodyModel(samp)
positionEstimator = ContactTrackingKalmanFilter(
SampledBodyModel.structureCopy(samp),
initialTime = spl.startTime,
initialPosition = spl.position(spl.startTime),
initialVelocity = spl.velocity(spl.startTime))
dt = 0.01
sampleTimes = np.arange(spl.startTime + dt, spl.endTime, dt)
for t in sampleTimes:
data = [{'jointName' : p.name,
'linearAcceleration' : p.acceleration(t)}
for p in spl.joints]
positionEstimator(data, t)
outdir = tempfile.mkdtemp()
filename = os.path.join(outdir, 'movie.avi')
autoPositionCamera()
renderSolenoidCoil(
SolenoidMagneticField(200,20,0.05,0.2, AffineTransform()))
createVideo(filename, [BodyModelRenderer(spl),
VelocityVectorRenderer(spl.getPoint('ltoes_end')),
ContactProbabilityRenderer(spl)],
spl.startTime, spl.startTime + 1, 3, (320, 200))
assert os.path.exists(filename)
shutil.rmtree(outdir)
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 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)
# IMUSim is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with IMUSim. If not, see <http://www.gnu.org/licenses/>.
from os import path
from imusim.io.bvh import loadBVHFile
from imusim.trajectories.rigid_body import SampledBodyModel, SplinedBodyModel
from imusim.algorithms import position
from imusim.testing.inspection import getImplementations
import numpy as np
referenceModel = SplinedBodyModel(
loadBVHFile(path.join(path.dirname(__file__), 'test.bvh'), 0.01))
dt = 0.01
sampleTimes = np.arange(referenceModel.startTime, referenceModel.endTime, dt)
def checkAlgorithm(algorithm):
sampledModel = SampledBodyModel.structureCopy(referenceModel)
for t in sampleTimes:
for referenceJoint, sampledJoint in zip(referenceModel.joints,
sampledModel.joints):
sampledJoint.rotationKeyFrames.add(t, referenceJoint.rotation(t))
positionEstimator = algorithm(
sampledModel,
initialTime=referenceModel.startTime,
# Create the simulation, load a splined body model of walking from existing mocap data that can be
# evaluated at any time.
sim = Simulation()
env = sim.environment
samplingPeriod = 1.0/800
oversampling = 16
# worst case for offsets is probably +/-1
accel_offset = 0
gyro_offset = 0
mag_offset = 0
probDrippedPacket = 0.0
transmissionPeriod = samplingPeriod * oversampling
print "transmission rate: ", 1 / transmissionPeriod, " Hz"
simModel = SplinedBodyModel(loadBVHFile('walk.bvh', conversionFactor=0.01))
sim.time = simModel.startTime
def angle(a,b):
return arccos(dot(a,b) / (l2norm(a) * l2norm(b)))
def setupIMU(id, joint):
# Set up an ideal IMU with the trajectory of the supplied joint, which samples at samplingPeriod.
imu = IdealIMU()
imu.simulation = sim
imu.trajectory = joint
def handleSample(behaviour):
pass
behaviour = BasicIMUBehaviour(imu, samplingPeriod, sampleCallback=handleSample, initialTime=sim.time)
