def calcQwt(self, qest, wt, delta_t):
print self.calcqqwt(qest, wt)
q1 = qest
cq1 = quat.conjugate(q1)
q2 = self.calcqqwt(qest, wt) * delta_t
cq2 = quat.conjugate(q2)
print q1 + q2
return 2
def test_conjugate():
# pmath.multiply(q0.numpy(), q1.numpy())
normalized = tq.normalize(torch.Tensor(rand_q(8)))
con = tq.conjugate(normalized)
for d in range(normalized.shape[0]):
con0 = tq.conjugate(normalized[d])
assert torch.all(con[d] == con0)
for d in range(normalized.shape[0]):
con0 = pmath.quaternion_conjugate(normalized[d].numpy())
assert np.all(con[d].numpy() == con0)
def CalibrationProcess(cal_pipe, client):
accel_points = SigmaPoints(.05**2, 12, 10)
compass_points = SigmaPoints(1.1**2, 28, 3)
norm = [0, 0, 1]
accel_calibration = RegisterCalibration(client, 'imu.accel', [[0, 0, 0, 1], 1])
compass_calibration = RegisterCalibration(client, 'imu.compass', [[0, 0, 0, 30, 0], [1, 1], 0])
client.watch('imu.alignmentQ')
if not cal_pipe: # get these through client rather than direct pipe
client.watch('imu.accel')
client.watch('imu.compass')
client.watch('imu.fusionQPose')
def debug(name):
def debug_by_name(*args):
s = ''
for a in args:
s += str(a) + ' '
client.set('imu.'+name+'.calibration.log', s)
return debug_by_name
last_compass_coverage = 0
while True:
t = time.monotonic()
addedpoint = False
down = False
while time.monotonic() - t < calibration_fit_period:
# receive pypilot messages
msg = client.receive(1)
for name in msg:
value = msg[name]
if name == 'imu.alignmentQ' and value:
norm = quaternion.rotvecquat([0, 0, 1], value)
compass_points.Reset()
elif name == 'imu.accel':
if value:
accel_points.AddPoint(value)
addedpoint = True
elif name == 'imu.compass' and down:
if value and down:
compass_points.AddPoint(value, down)
addedpoint = True
elif name == 'imu.fusionQPose':
if value:
down = quaternion.rotvecquat([0, 0, 1], quaternion.conjugate(value))
# receive calibration data
if cal_pipe:
p = cal_pipe.recv()
while p:
if 'accel' in p:
accel_points.AddPoint(p['accel'])
addedpoint = True
if 'compass' in p:
down = quaternion.rotvecquat([0, 0, 1], quaternion.conjugate(p['fusionQPose']))
compass_points.AddPoint(p['compass'], down)
addedpoint = True
p = cal_pipe.recv()
cals = [(accel_calibration, accel_points), (compass_calibration, compass_points)]
for calibration, points in cals:
calibration.age.update()
if points.Updated():
calibration.sigmapoints.set(points.Points())
if not addedpoint: # don't bother to run fit if no new data
continue
accel_points.RemoveOlder(10*60) # 10 minutes
fit = FitAccel(debug('accel'), accel_points)
if fit: # reset compass sigmapoints on accel cal
dist = vector.dist(fit[0][:3], accel_calibration.value[0][:3])
if dist > .01: # only update when bias changes more than this
if dist > .08: # reset compass cal from large change in accel bias
compass_points.Reset()
debug('accel')('reset compass from large accel bias')
accel_calibration.set(fit)
accel_calibration.points.set(accel_points.Points())
else:
debug('accel')('calibration distance too small ', dist)
compass_points.RemoveOlder(20*60) # 20 minutes
fit = FitCompass(debug('compass'), compass_points, compass_calibration.value[0], norm)
if fit:
# ignore decreasing compass coverage
new_coverage = fit[1][2]
if new_coverage < last_compass_coverage:
debug('compass')('ignoring decreasing coverage')
else:
compass_calibration.set(fit)
compass_calibration.points.set(compass_points.Points())
else:
last_compass_coverage = 0 # reset
def IMURead(self):
data = False
while self.poller.poll(0): # read all the data from the pipe
data = self.imu_pipe.recv()
if not data:
if time.time() - self.last_imuread > 1 and self.loopfreq.value:
print 'IMURead failed!'
self.loopfreq.set(0)
for name in self.SensorValues:
self.SensorValues[name].set(False)
self.uptime.reset()
return False
if vector.norm(data['accel']) == 0:
print 'vector n', data['accel']
return False
self.last_imuread = time.time()
self.loopfreq.strobe()
if not self.FirstTimeStamp:
self.FirstTimeStamp = data['timestamp']
data['timestamp'] -= self.FirstTimeStamp
#data['accel_comp'] = quaternion.rotvecquat(vector.sub(data['accel'], down), self.alignmentQ.value)
# apply alignment calibration
gyro_q = quaternion.rotvecquat(data['gyro'], data['fusionQPose'])
data['pitchrate'], data['rollrate'], data['headingrate'] = map(
math.degrees, gyro_q)
origfusionQPose = data['fusionQPose']
aligned = quaternion.multiply(data['fusionQPose'],
self.alignmentQ.value)
data['fusionQPose'] = quaternion.normalize(
aligned) # floating point precision errors
data['roll'], data['pitch'], data['heading'] = map(
math.degrees, quaternion.toeuler(data['fusionQPose']))
if data['heading'] < 0:
data['heading'] += 360
dt = data['timestamp'] - self.lasttimestamp
self.lasttimestamp = data['timestamp']
if dt > .02 and dt < .5:
data['headingraterate'] = (data['headingrate'] -
self.headingrate) / dt
else:
data['headingraterate'] = 0
self.headingrate = data['headingrate']
data['heel'] = self.heel = data['roll'] * .03 + self.heel * .97
#data['roll'] -= data['heel']
data['gyro'] = list(map(math.degrees, data['gyro']))
data['gyrobias'] = list(map(math.degrees, data['gyrobias']))
# lowpass heading and rate
llp = self.heading_lowpass_constant.value
data['heading_lowpass'] = heading_filter(
llp, data['heading'], self.SensorValues['heading_lowpass'].value)
llp = self.headingrate_lowpass_constant.value
data['headingrate_lowpass'] = llp * data['headingrate'] + (
1 - llp) * self.SensorValues['headingrate_lowpass'].value
llp = self.headingraterate_lowpass_constant.value
data['headingraterate_lowpass'] = llp * data['headingraterate'] + (
1 - llp) * self.SensorValues['headingraterate_lowpass'].value
# set sensors
self.server.TimeStamp('imu', data['timestamp'])
for name in self.SensorValues:
self.SensorValues[name].set(data[name])
compass, accel, down = False, False, False
if not self.accel_calibration.locked.value:
accel = list(data['accel'])
if not self.compass_calibration.locked.value:
down = quaternion.rotvecquat([0, 0, 1],
quaternion.conjugate(origfusionQPose))
compass = list(data['compass']) + down
if accel or compass:
self.auto_cal.AddPoint((accel, compass, down))
self.uptime.update()
# count down to alignment
if self.alignmentCounter.value != self.last_alignmentCounter:
self.alignmentPose = [0, 0, 0, 0]
if self.alignmentCounter.value > 0:
self.alignmentPose = list(
map(lambda x, y: x + y, self.alignmentPose,
data['fusionQPose']))
self.alignmentCounter.set(self.alignmentCounter.value - 1)
if self.alignmentCounter.value == 0:
self.alignmentPose = quaternion.normalize(self.alignmentPose)
adown = quaternion.rotvecquat([0, 0, 1],
quaternion.conjugate(
self.alignmentPose))
alignment = []
alignment = quaternion.vec2vec2quat([0, 0, 1], adown)
alignment = quaternion.multiply(self.alignmentQ.value,
alignment)
if len(alignment):
self.update_alignment(alignment)
self.last_alignmentCounter = self.alignmentCounter.value
if self.heading_off.value != self.last_heading_off:
self.update_alignment(self.alignmentQ.value)
self.last_heading_off = self.heading_off.value
result = self.auto_cal.UpdatedCalibration()
if result:
if result[0] == 'accel' and not self.accel_calibration.locked.value:
#print '[boatimu] cal result', result[0]
self.accel_calibration.sigmapoints.set(result[2])
if result[1]:
self.accel_calibration.age.reset()
self.accel_calibration.set(result[1])
elif result[
0] == 'compass' and not self.compass_calibration.locked.value:
#print '[boatimu] cal result', result[0]
self.compass_calibration.sigmapoints.set(result[2])
if result[1]:
self.compass_calibration.age.reset()
self.compass_calibration.set(result[1])
self.accel_calibration.age.update()
self.compass_calibration.age.update()
return data
def integrate_all(self, use_acc=False):
"""go through each gyro sample and integrate to find orientation
Returns:
(np.ndarray, np.ndarray): tuple (time_list, quaternion orientation array)
"""
if self.already_integrated and (use_acc == self.last_used_acc
or not self.acc_available):
return (self.time_list, self.orientation_list)
apply_complementary = self.acc_available and use_acc
self.last_used_acc = use_acc
if apply_complementary:
# find valid accelation data points
#print(self.acc)
#print(self.acc.shape)
asquared = np.sum(self.acc[:, 1:]**2, 1)
# between 0.9 and 1.1 g
complementary_mask = np.logical_and(0.81 < asquared,
asquared < 1.21)
self.orientation = np.copy(self.initial_orientation)
# temp lists to save data
temp_orientation_list = []
temp_time_list = []
start_time = self.gyro[0][0] # seconds
for i in range(self.num_data_points):
# angular velocity vector
omega = self.gyro[i][1:]
# get current and adjecent times
last_time = self.gyro[i - 1][0] if i > 0 else self.gyro[i][0]
this_time = self.gyro[i][0]
next_time = self.gyro[
i + 1][0] if i < self.num_data_points - 1 else self.gyro[i][0]
# symmetrical dt calculation. Should give slightly better results when missing data
delta_time = (next_time - last_time) / 2
# Only calculate if angular velocity is present
if np.any(omega) or apply_complementary:
# complementary filter
if apply_complementary:
if complementary_mask[i]:
avec = self.acc[i][1:]
avec /= np.linalg.norm(avec)
accWorldVec = quat.rotate_vector_fast(
self.orientation, avec)
correctionWorld = np.cross(accWorldVec, self.grav_vec)
# high weight for first two seconds to "lock" it, then
weight = 10 if this_time - start_time < 1.5 else 0.6
correctionBody = weight * quat.rotate_vector_fast(
quat.conjugate(self.orientation), correctionWorld)
omega = omega + correctionBody
# calculate rotation quaternion
delta_q = self.rate_to_quat(omega, delta_time)
# rotate orientation by this quaternion
self.orientation = quat.quaternion_multiply(
self.orientation, delta_q) # Maybe change order
self.orientation = quat.normalize(self.orientation)
temp_orientation_list.append(np.copy(self.orientation))
temp_time_list.append(this_time)
self.orientation_list = np.array(temp_orientation_list)
self.time_list = np.array(temp_time_list)
self.already_integrated = True
return (self.time_list, self.orientation_list)
def read(self):
data = self.IMUread()
if not data:
if time.monotonic(
) - self.last_imuread > 1 and self.frequency.value:
print('IMURead failed!')
self.frequency.set(False)
for name in self.SensorValues:
self.SensorValues[name].set(False)
self.uptime.reset()
return False
if vector.norm(data['accel']) == 0:
print('accel values invalid', data['accel'])
return False
self.last_imuread = time.monotonic()
self.frequency.strobe()
# apply alignment calibration
gyro_q = quaternion.rotvecquat(data['gyro'], data['fusionQPose'])
data['pitchrate'], data['rollrate'], data['headingrate'] = map(
math.degrees, gyro_q)
aligned = quaternion.multiply(data['fusionQPose'],
self.alignmentQ.value)
aligned = quaternion.normalize(
aligned) # floating point precision errors
data['roll'], data['pitch'], data['heading'] = map(
math.degrees, quaternion.toeuler(aligned))
if data['heading'] < 0:
data['heading'] += 360
dt = data['timestamp'] - self.lasttimestamp
self.lasttimestamp = data['timestamp']
if dt > .01 and dt < .2:
data['headingraterate'] = (data['headingrate'] -
self.headingrate) / dt
else:
data['headingraterate'] = 0
self.headingrate = data['headingrate']
data['heel'] = self.heel = data['roll'] * .03 + self.heel * .97
#data['roll'] -= data['heel']
data['gyro'] = list(map(math.degrees, data['gyro']))
# lowpass heading and rate
llp = self.heading_lowpass_constant.value
data['heading_lowpass'] = heading_filter(
llp, data['heading'], self.SensorValues['heading_lowpass'].value)
llp = self.headingrate_lowpass_constant.value
data['headingrate_lowpass'] = llp * data['headingrate'] + (
1 - llp) * self.SensorValues['headingrate_lowpass'].value
llp = self.headingraterate_lowpass_constant.value
data['headingraterate_lowpass'] = llp * data['headingraterate'] + (
1 - llp) * self.SensorValues['headingraterate_lowpass'].value
# set sensors
for name in self.SensorValues:
self.SensorValues[name].set(data[name])
self.uptime.update()
# count down to alignment
if self.alignmentCounter.value != self.last_alignmentCounter:
self.alignmentPose = [0, 0, 0, 0]
if self.alignmentCounter.value > 0:
self.alignmentPose = list(
map(lambda x, y: x + y, self.alignmentPose, aligned))
self.alignmentCounter.set(self.alignmentCounter.value - 1)
if self.alignmentCounter.value == 0:
self.alignmentPose = quaternion.normalize(self.alignmentPose)
adown = quaternion.rotvecquat([0, 0, 1],
quaternion.conjugate(
self.alignmentPose))
alignment = []
alignment = quaternion.vec2vec2quat([0, 0, 1], adown)
alignment = quaternion.multiply(self.alignmentQ.value,
alignment)
if len(alignment):
self.update_alignment(alignment)
self.last_alignmentCounter = self.alignmentCounter.value
# if alignment or heading offset changed:
if self.heading_off.value != self.heading_off.last or \
self.alignmentQ.value != self.alignmentQ.last:
self.update_alignment(self.alignmentQ.value)
self.heading_off.last = self.heading_off.value
self.alignmentQ.last = self.alignmentQ.value
if self.auto_cal.cal_pipe:
#print('warning, cal pipe always sending despite locks')
cal_data = {}
#how to check this here?? if not 'imu.accel.calibration.locked'
cal_data['accel'] = list(data['accel'])
#how to check this here?? if not 'imu.compass.calibration.locked'
cal_data['compass'] = list(data['compass'])
cal_data['fusionQPose'] = list(data['fusionQPose'])
if cal_data:
#print('send', cal_data)
self.auto_cal.cal_pipe.send(cal_data)
return data
def IMURead(self):
data = False
while self.poller.poll(0): # read all the data from the pipe
data = self.imu_pipe.recv()
if not data:
if time.time() - self.last_imuread > 1 and self.loopfreq.value:
print('IMURead failed!')
self.loopfreq.set(0)
for name in self.SensorValues:
self.SensorValues[name].set(False)
self.uptime.reset()
return False
if vector.norm(data['accel']) == 0:
print('accel values invalid', data['accel'])
return False
t = time.time()
self.timestamp.set(t - self.starttime)
self.last_imuread = t
self.loopfreq.strobe()
# apply alignment calibration
gyro_q = quaternion.rotvecquat(data['gyro'], data['fusionQPose'])
data['pitchrate'], data['rollrate'], data['headingrate'] = map(
math.degrees, gyro_q)
origfusionQPose = data['fusionQPose']
aligned = quaternion.multiply(data['fusionQPose'],
self.alignmentQ.value)
data['fusionQPose'] = quaternion.normalize(
aligned) # floating point precision errors
data['roll'], data['pitch'], data['heading'] = map(
math.degrees, quaternion.toeuler(data['fusionQPose']))
if data['heading'] < 0:
data['heading'] += 360
dt = data['timestamp'] - self.lasttimestamp
self.lasttimestamp = data['timestamp']
if dt > .02 and dt < .5:
data['headingraterate'] = (data['headingrate'] -
self.headingrate) / dt
else:
data['headingraterate'] = 0
self.headingrate = data['headingrate']
data['heel'] = self.heel = data['roll'] * .03 + self.heel * .97
#data['roll'] -= data['heel']
data['gyro'] = list(map(math.degrees, data['gyro']))
data['gyrobias'] = list(map(math.degrees, data['gyrobias']))
# lowpass heading and rate
llp = self.heading_lowpass_constant.value
data['heading_lowpass'] = heading_filter(
llp, data['heading'], self.SensorValues['heading_lowpass'].value)
llp = self.headingrate_lowpass_constant.value
data['headingrate_lowpass'] = llp * data['headingrate'] + (
1 - llp) * self.SensorValues['headingrate_lowpass'].value
llp = self.headingraterate_lowpass_constant.value
data['headingraterate_lowpass'] = llp * data['headingraterate'] + (
1 - llp) * self.SensorValues['headingraterate_lowpass'].value
# set sensors
for name in self.SensorValues:
self.SensorValues[name].set(data[name])
self.uptime.update()
# count down to alignment
if self.alignmentCounter.value != self.last_alignmentCounter:
self.alignmentPose = [0, 0, 0, 0]
if self.alignmentCounter.value > 0:
self.alignmentPose = list(
map(lambda x, y: x + y, self.alignmentPose,
data['fusionQPose']))
self.alignmentCounter.set(self.alignmentCounter.value - 1)
if self.alignmentCounter.value == 0:
self.alignmentPose = quaternion.normalize(self.alignmentPose)
adown = quaternion.rotvecquat([0, 0, 1],
quaternion.conjugate(
self.alignmentPose))
alignment = []
alignment = quaternion.vec2vec2quat([0, 0, 1], adown)
alignment = quaternion.multiply(self.alignmentQ.value,
alignment)
if len(alignment):
self.update_alignment(alignment)
self.last_alignmentCounter = self.alignmentCounter.value
# if alignment or heading offset changed:
if self.heading_off.value != self.heading_off.last or self.alignmentQ.value != self.alignmentQ.last:
self.update_alignment(self.alignmentQ.value)
self.heading_off.last = self.heading_off.value
self.alignmentQ.last = self.alignmentQ.value
cal_data = {}
if not self.accel_calibration.locked.value:
cal_data['accel'] = list(data['accel'])
if not self.compass_calibration.locked.value:
cal_data['compass'] = list(data['compass'])
cal_data['down'] = quaternion.rotvecquat(
[0, 0, 1], quaternion.conjugate(origfusionQPose))
if cal_data:
self.auto_cal.cal_pipe.send(cal_data)
self.accel_calibration.age.update()
self.compass_calibration.age.update()
return data