clean up and refactoring to use custom preintegration params

gtsam/navigation/navigation.i

@@ -88,6 +88,8 @@ virtual class PreintegratedRotationParams {
 virtual class PreintegrationParams : gtsam::PreintegratedRotationParams {
   PreintegrationParams(Vector n_gravity);
 
+  gtsam::Vector n_gravity;
+
   static gtsam::PreintegrationParams* MakeSharedD(double g);
   static gtsam::PreintegrationParams* MakeSharedU(double g);
   static gtsam::PreintegrationParams* MakeSharedD();  // default g = 9.81

python/gtsam/examples/ImuFactorExample.py

@@ -10,20 +10,19 @@ A script validating and demonstrating the ImuFactor inference.
 Author: Frank Dellaert, Varun Agrawal
 """
 
-# pylint: disable=no-name-in-module,unused-import,arguments-differ
+# pylint: disable=no-name-in-module,unused-import,arguments-differ,import-error,wrong-import-order
 
 from __future__ import print_function
 
 import argparse
 import math
 
+import gtsam
 import matplotlib.pyplot as plt
 import numpy as np
-from mpl_toolkits.mplot3d import Axes3D
-
-import gtsam
 from gtsam.symbol_shorthand import B, V, X
 from gtsam.utils.plot import plot_pose3
+from mpl_toolkits.mplot3d import Axes3D
 
 from PreintegrationExample import POSES_FIG, PreintegrationExample
 
@@ -51,12 +50,23 @@ class ImuFactorExample(PreintegrationExample):
         gyroBias = np.array([0.1, 0.3, -0.1])
         bias = gtsam.imuBias.ConstantBias(accBias, gyroBias)
 
+        g = 9.81
+        params = gtsam.PreintegrationParams.MakeSharedU(g)
+
+        # Some arbitrary noise sigmas
+        gyro_sigma = 1e-3
+        accel_sigma = 1e-3
+        I_3x3 = np.eye(3)
+        params.setGyroscopeCovariance(gyro_sigma**2 * I_3x3)
+        params.setAccelerometerCovariance(accel_sigma**2 * I_3x3)
+        params.setIntegrationCovariance(1e-7**2 * I_3x3)
+
         dt = 1e-2
         super(ImuFactorExample, self).__init__(twist_scenarios[twist_scenario],
-                                               bias, dt)
+                                               bias, params, dt)
 
     def addPrior(self, i, graph):
-        """Add priors at time step `i`."""
+        """Add a prior on the navigation state at time `i`."""
         state = self.scenario.navState(i)
         graph.push_back(
             gtsam.PriorFactorPose3(X(i), state.pose(), self.priorNoise))
@@ -71,20 +81,26 @@ class ImuFactorExample(PreintegrationExample):
         result = optimizer.optimize()
         return result
 
-    def plot(self, result):
+    def plot(self,
-        """Plot resulting poses."""
+             values,
+             title="Estimated Trajectory",
+             fignum=POSES_FIG + 1,
+             show=False):
+        """Plot poses in values."""
         i = 0
-        while result.exists(X(i)):
+        while values.exists(X(i)):
-            pose_i = result.atPose3(X(i))
+            pose_i = values.atPose3(X(i))
-            plot_pose3(POSES_FIG + 1, pose_i, 1)
+            plot_pose3(fignum, pose_i, 1)
             i += 1
-        plt.title("Estimated Trajectory")
+        plt.title(title)
 
-        gtsam.utils.plot.set_axes_equal(POSES_FIG + 1)
+        gtsam.utils.plot.set_axes_equal(fignum)
 
-        print("Bias Values", result.atConstantBias(BIAS_KEY))
+        print("Bias Values", values.atConstantBias(BIAS_KEY))
 
         plt.ioff()
+
+        if show:
             plt.show()
 
     def run(self, T=12, compute_covariances=False, verbose=True):
@@ -173,7 +189,7 @@ class ImuFactorExample(PreintegrationExample):
                 print("Covariance on vel {}:\n{}\n".format(
                     i, marginals.marginalCovariance(V(i))))
 
-        self.plot(result)
+        self.plot(result, show=True)
 
 
 if __name__ == '__main__':

python/gtsam/examples/PreintegrationExample.py

@@ -5,9 +5,13 @@ All Rights Reserved
 
 See LICENSE for the license information
 
-A script validating the Preintegration of IMU measurements
+A script validating the Preintegration of IMU measurements.
+
+Authors: Frank Dellaert, Varun Agrawal.
 """
 
+# pylint: disable=invalid-name,unused-import,wrong-import-order
+
 import math
 
 import gtsam
@@ -21,22 +25,20 @@ POSES_FIG = 2
 
 
 class PreintegrationExample(object):
-
+    """Base class for all preintegration examples."""
     @staticmethod
     def defaultParams(g):
         """Create default parameters with Z *up* and realistic noise parameters"""
         params = gtsam.PreintegrationParams.MakeSharedU(g)
         kGyroSigma = math.radians(0.5) / 60  # 0.5 degree ARW
         kAccelSigma = 0.1 / 60  # 10 cm VRW
-        params.setGyroscopeCovariance(
+        params.setGyroscopeCovariance(kGyroSigma**2 * np.identity(3, float))
-            kGyroSigma ** 2 * np.identity(3, float))
+        params.setAccelerometerCovariance(kAccelSigma**2 *
-        params.setAccelerometerCovariance(
+                                          np.identity(3, float))
-            kAccelSigma ** 2 * np.identity(3, float))
+        params.setIntegrationCovariance(0.0000001**2 * np.identity(3, float))
-        params.setIntegrationCovariance(
-            0.0000001 ** 2 * np.identity(3, float))
         return params
 
-    def __init__(self, twist=None, bias=None, dt=1e-2):
+    def __init__(self, twist=None, bias=None, params=None, dt=1e-2):
         """Initialize with given twist, a pair(angularVelocityVector, velocityVector)."""
 
         # setup interactive plotting
@@ -58,9 +60,11 @@ class PreintegrationExample(object):
         self.labels = list('xyz')
         self.colors = list('rgb')
 
-        # Create runner
+        if params:
-        self.g = 10  # simple gravity constant
+            self.params = params
-        self.params = self.defaultParams(self.g)
+        else:
+            # Default params with simple gravity constant
+            self.params = self.defaultParams(g=10)
 
         if bias is not None:
             self.actualBias = bias
@@ -69,13 +73,15 @@ class PreintegrationExample(object):
             gyroBias = np.array([0, 0, 0])
             self.actualBias = gtsam.imuBias.ConstantBias(accBias, gyroBias)
 
-        self.runner = gtsam.ScenarioRunner(
+        # Create runner
-            self.scenario, self.params, self.dt, self.actualBias)
+        self.runner = gtsam.ScenarioRunner(self.scenario, self.params, self.dt,
+                                           self.actualBias)
 
         fig, self.axes = plt.subplots(4, 3)
         fig.set_tight_layout(True)
 
     def plotImu(self, t, measuredOmega, measuredAcc):
+        """Plot IMU measurements."""
         plt.figure(IMU_FIG)
 
         # plot angular velocity
@@ -109,7 +115,7 @@ class PreintegrationExample(object):
             ax.set_xlabel('specific force ' + label)
 
     def plotGroundTruthPose(self, t, scale=0.3, time_interval=0.01):
-        # plot ground truth pose, as well as prediction from integrated IMU measurements
+        """Plot ground truth pose, as well as prediction from integrated IMU measurements."""
         actualPose = self.scenario.pose(t)
         plot_pose3(POSES_FIG, actualPose, scale)
         t = actualPose.translation()
@@ -122,7 +128,7 @@ class PreintegrationExample(object):
         plt.pause(time_interval)
 
     def run(self, T=12):
-        # simulate the loop
+        """Simulate the loop."""
         for i, t in enumerate(np.arange(0, T, self.dt)):
             measuredOmega = self.runner.measuredAngularVelocity(t)
             measuredAcc = self.runner.measuredSpecificForce(t)