Sync ImuFactorExample2
Fan Jiang
parent
2bda74950a
commit
48b0c845dc
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@ -8,22 +8,20 @@ from __future__ import print_function
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import math
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import matplotlib.pyplot as plt
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import numpy as np
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from mpl_toolkits.mplot3d import Axes3D # pylint: disable=W0611
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import gtsam
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import gtsam.utils.plot as gtsam_plot
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def X(key):
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"""Create symbol for pose key."""
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return gtsam.symbol('x', key)
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def V(key):
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"""Create symbol for velocity key."""
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return gtsam.symbol('v', key)
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import matplotlib.pyplot as plt
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import numpy as np
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from gtsam import (ISAM2, BetweenFactorConstantBias, Cal3_S2,
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ConstantTwistScenario, ImuFactor, NonlinearFactorGraph,
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PinholeCameraCal3_S2, Point3, Pose3,
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PriorFactorConstantBias, PriorFactorPose3,
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PriorFactorVector, Rot3, Values)
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from gtsam import symbol_shorthand
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B = symbol_shorthand.B
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V = symbol_shorthand.V
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X = symbol_shorthand.X
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from mpl_toolkits.mplot3d import Axes3D # pylint: disable=W0611
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def vector3(x, y, z):
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@ -69,20 +67,19 @@ PARAMS.setUse2ndOrderCoriolis(False)
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PARAMS.setOmegaCoriolis(vector3(0, 0, 0))
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BIAS_COVARIANCE = gtsam.noiseModel.Isotropic.Variance(6, 0.1)
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DELTA = gtsam.Pose3(gtsam.Rot3.Rodrigues(0, 0, 0),
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gtsam.Point3(0.05, -0.10, 0.20))
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DELTA = Pose3(Rot3.Rodrigues(0, 0, 0),
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Point3(0.05, -0.10, 0.20))
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def IMU_example():
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"""Run iSAM 2 example with IMU factor."""
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ZERO_BIAS = gtsam.imuBias.ConstantBias()
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# Start with a camera on x-axis looking at origin
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radius = 30
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up = gtsam.Point3(0, 0, 1)
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target = gtsam.Point3(0, 0, 0)
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position = gtsam.Point3(radius, 0, 0)
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camera = gtsam.SimpleCamera.Lookat(position, target, up, gtsam.Cal3_S2())
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up = Point3(0, 0, 1)
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target = Point3(0, 0, 0)
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position = Point3(radius, 0, 0)
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camera = PinholeCameraCal3_S2.Lookat(position, target, up, Cal3_S2())
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pose_0 = camera.pose()
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# Create the set of ground-truth landmarks and poses
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@ -91,37 +88,37 @@ def IMU_example():
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angular_velocity_vector = vector3(0, -angular_velocity, 0)
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linear_velocity_vector = vector3(radius * angular_velocity, 0, 0)
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scenario = gtsam.ConstantTwistScenario(
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scenario = ConstantTwistScenario(
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angular_velocity_vector, linear_velocity_vector, pose_0)
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# Create a factor graph
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newgraph = gtsam.NonlinearFactorGraph()
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newgraph = NonlinearFactorGraph()
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# Create (incremental) ISAM2 solver
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isam = gtsam.ISAM2()
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isam = ISAM2()
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# Create the initial estimate to the solution
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# Intentionally initialize the variables off from the ground truth
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initialEstimate = gtsam.Values()
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initialEstimate = Values()
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# Add a prior on pose x0. This indirectly specifies where the origin is.
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# 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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noise = gtsam.noiseModel.Diagonal.Sigmas(
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np.array([0.1, 0.1, 0.1, 0.3, 0.3, 0.3]))
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newgraph.push_back(gtsam.PriorFactorPose3(X(0), pose_0, noise))
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newgraph.push_back(PriorFactorPose3(X(0), pose_0, noise))
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# Add imu priors
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biasKey = gtsam.symbol('b', 0)
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biasKey = B(0)
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biasnoise = gtsam.noiseModel.Isotropic.Sigma(6, 0.1)
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biasprior = gtsam.PriorFactorConstantBias(biasKey, ZERO_BIAS,
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biasnoise)
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biasprior = PriorFactorConstantBias(biasKey, gtsam.imuBias.ConstantBias(),
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biasnoise)
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newgraph.push_back(biasprior)
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initialEstimate.insert(biasKey, ZERO_BIAS)
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initialEstimate.insert(biasKey, gtsam.imuBias.ConstantBias())
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velnoise = gtsam.noiseModel.Isotropic.Sigma(3, 0.1)
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# Calculate with correct initial velocity
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n_velocity = vector3(0, angular_velocity * radius, 0)
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velprior = gtsam.PriorFactorVector(V(0), n_velocity, velnoise)
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velprior = PriorFactorVector(V(0), n_velocity, velnoise)
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newgraph.push_back(velprior)
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initialEstimate.insert(V(0), n_velocity)
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@ -142,10 +139,10 @@ def IMU_example():
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# Add Bias variables periodically
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if i % 5 == 0:
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biasKey += 1
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factor = gtsam.BetweenFactorConstantBias(
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biasKey - 1, biasKey, ZERO_BIAS, BIAS_COVARIANCE)
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factor = BetweenFactorConstantBias(
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biasKey - 1, biasKey, gtsam.imuBias.ConstantBias(), BIAS_COVARIANCE)
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newgraph.add(factor)
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initialEstimate.insert(biasKey, ZERO_BIAS)
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initialEstimate.insert(biasKey, gtsam.imuBias.ConstantBias())
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# Predict acceleration and gyro measurements in (actual) body frame
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nRb = scenario.rotation(t).matrix()
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@ -155,8 +152,7 @@ def IMU_example():
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accum.integrateMeasurement(measuredAcc, measuredOmega, delta_t)
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# Add Imu Factor
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imufac = gtsam.ImuFactor(
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X(i - 1), V(i - 1), X(i), V(i), biasKey, accum)
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imufac = ImuFactor(X(i - 1), V(i - 1), X(i), V(i), biasKey, accum)
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newgraph.add(imufac)
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# insert new velocity, which is wrong
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@ -169,7 +165,7 @@ def IMU_example():
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ISAM2_plot(result)
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# reset
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newgraph = gtsam.NonlinearFactorGraph()
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newgraph = NonlinearFactorGraph()
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initialEstimate.clear()
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