diff --git a/python/gtsam_py/python/examples/ImuFactorExample2.py b/python/gtsam_py/python/examples/ImuFactorExample2.py index d5be69f47..969d4fe6b 100644 --- a/python/gtsam_py/python/examples/ImuFactorExample2.py +++ b/python/gtsam_py/python/examples/ImuFactorExample2.py @@ -1,6 +1,6 @@ """ iSAM2 example with ImuFactor. -Author: Robert Truax (C++), Frank Dellaert (Python) +Author: Frank Dellaert, Varun Agrawal """ # pylint: disable=invalid-name, E1101 @@ -8,17 +8,18 @@ from __future__ import print_function import math -import gtsam -import gtsam.utils.plot as gtsam_plot import matplotlib.pyplot as plt +from mpl_toolkits.mplot3d import Axes3D # pylint: disable=W0611 import numpy as np + +import gtsam from gtsam import (ISAM2, BetweenFactorConstantBias, Cal3_S2, ConstantTwistScenario, ImuFactor, NonlinearFactorGraph, PinholeCameraCal3_S2, Point3, Pose3, PriorFactorConstantBias, PriorFactorPose3, PriorFactorVector, Rot3, Values) from gtsam.gtsam.symbol_shorthand import B, V, X -from mpl_toolkits.mplot3d import Axes3D # pylint: disable=W0611 +from gtsam.utils import plot def vector3(x, y, z): @@ -26,46 +27,45 @@ def vector3(x, y, z): return np.array([x, y, z], dtype=np.float) -def ISAM2_plot(values, fignum=0): - """Plot poses.""" - fig = plt.figure(fignum) - axes = fig.gca(projection='3d') - plt.cla() - - i = 0 - min_bounds = 0, 0, 0 - max_bounds = 0, 0, 0 - while values.exists(X(i)): - pose_i = values.atPose3(X(i)) - gtsam_plot.plot_pose3(fignum, pose_i, 10) - position = pose_i.translation() - min_bounds = [min(v1, v2) for (v1, v2) in zip(position, min_bounds)] - max_bounds = [max(v1, v2) for (v1, v2) in zip(position, max_bounds)] - # max_bounds = min(pose_i.x(), max_bounds[0]), 0, 0 - i += 1 - - # draw - axes.set_xlim3d(min_bounds[0]-1, max_bounds[0]+1) - axes.set_ylim3d(min_bounds[1]-1, max_bounds[1]+1) - axes.set_zlim3d(min_bounds[2]-1, max_bounds[2]+1) - plt.pause(1) - - -# IMU preintegration parameters -# Default Params for a Z-up navigation frame, such as ENU: gravity points along negative Z-axis g = 9.81 n_gravity = vector3(0, 0, -g) -PARAMS = gtsam.PreintegrationParams.MakeSharedU(g) -I = np.eye(3) -PARAMS.setAccelerometerCovariance(I * 0.1) -PARAMS.setGyroscopeCovariance(I * 0.1) -PARAMS.setIntegrationCovariance(I * 0.1) -PARAMS.setUse2ndOrderCoriolis(False) -PARAMS.setOmegaCoriolis(vector3(0, 0, 0)) -BIAS_COVARIANCE = gtsam.noiseModel.Isotropic.Variance(6, 0.1) -DELTA = Pose3(Rot3.Rodrigues(0, 0, 0), - Point3(0.05, -0.10, 0.20)) + +def preintegration_parameters(): + # IMU preintegration parameters + # Default Params for a Z-up navigation frame, such as ENU: gravity points along negative Z-axis + PARAMS = gtsam.PreintegrationParams.MakeSharedU(g) + I = np.eye(3) + PARAMS.setAccelerometerCovariance(I * 0.1) + PARAMS.setGyroscopeCovariance(I * 0.1) + PARAMS.setIntegrationCovariance(I * 0.1) + PARAMS.setUse2ndOrderCoriolis(False) + PARAMS.setOmegaCoriolis(vector3(0, 0, 0)) + + BIAS_COVARIANCE = gtsam.noiseModel.Isotropic.Variance(6, 0.1) + DELTA = Pose3(Rot3.Rodrigues(0, 0, 0), + Point3(0.05, -0.10, 0.20)) + + return PARAMS, BIAS_COVARIANCE, DELTA + + +def get_camera(radius): + up = Point3(0, 0, 1) + target = Point3(0, 0, 0) + position = Point3(radius, 0, 0) + camera = PinholeCameraCal3_S2.Lookat(position, target, up, Cal3_S2()) + return camera + + +def get_scenario(radius, pose_0, angular_velocity, delta_t): + """Create the set of ground-truth landmarks and poses""" + + angular_velocity_vector = vector3(0, -angular_velocity, 0) + linear_velocity_vector = vector3(radius * angular_velocity, 0, 0) + scenario = ConstantTwistScenario( + angular_velocity_vector, linear_velocity_vector, pose_0) + + return scenario def IMU_example(): @@ -73,23 +73,17 @@ def IMU_example(): # Start with a camera on x-axis looking at origin radius = 30 - up = Point3(0, 0, 1) - target = Point3(0, 0, 0) - position = Point3(radius, 0, 0) - camera = PinholeCameraCal3_S2.Lookat(position, target, up, Cal3_S2()) + camera = get_camera(radius) pose_0 = camera.pose() - # Create the set of ground-truth landmarks and poses - angular_velocity = math.radians(180) # rad/sec delta_t = 1.0/18 # makes for 10 degrees per step + angular_velocity = math.radians(180) # rad/sec + scenario = get_scenario(radius, pose_0, angular_velocity, delta_t) - angular_velocity_vector = vector3(0, -angular_velocity, 0) - linear_velocity_vector = vector3(radius * angular_velocity, 0, 0) - scenario = ConstantTwistScenario( - angular_velocity_vector, linear_velocity_vector, pose_0) + PARAMS, BIAS_COVARIANCE, DELTA = preintegration_parameters() # Create a factor graph - newgraph = NonlinearFactorGraph() + graph = NonlinearFactorGraph() # Create (incremental) ISAM2 solver isam = ISAM2() @@ -102,21 +96,21 @@ def IMU_example(): # 30cm std on x,y,z 0.1 rad on roll,pitch,yaw noise = gtsam.noiseModel.Diagonal.Sigmas( np.array([0.1, 0.1, 0.1, 0.3, 0.3, 0.3])) - newgraph.push_back(PriorFactorPose3(X(0), pose_0, noise)) + graph.push_back(PriorFactorPose3(X(0), pose_0, noise)) # Add imu priors biasKey = B(0) biasnoise = gtsam.noiseModel.Isotropic.Sigma(6, 0.1) biasprior = PriorFactorConstantBias(biasKey, gtsam.imuBias.ConstantBias(), biasnoise) - newgraph.push_back(biasprior) + graph.push_back(biasprior) initialEstimate.insert(biasKey, gtsam.imuBias.ConstantBias()) velnoise = gtsam.noiseModel.Isotropic.Sigma(3, 0.1) # Calculate with correct initial velocity n_velocity = vector3(0, angular_velocity * radius, 0) velprior = PriorFactorVector(V(0), n_velocity, velnoise) - newgraph.push_back(velprior) + graph.push_back(velprior) initialEstimate.insert(V(0), n_velocity) accum = gtsam.PreintegratedImuMeasurements(PARAMS) @@ -138,7 +132,7 @@ def IMU_example(): biasKey += 1 factor = BetweenFactorConstantBias( biasKey - 1, biasKey, gtsam.imuBias.ConstantBias(), BIAS_COVARIANCE) - newgraph.add(factor) + graph.add(factor) initialEstimate.insert(biasKey, gtsam.imuBias.ConstantBias()) # Predict acceleration and gyro measurements in (actual) body frame @@ -150,21 +144,24 @@ def IMU_example(): # Add Imu Factor imufac = ImuFactor(X(i - 1), V(i - 1), X(i), V(i), biasKey, accum) - newgraph.add(imufac) + graph.add(imufac) # insert new velocity, which is wrong initialEstimate.insert(V(i), n_velocity) accum.resetIntegration() # Incremental solution - isam.update(newgraph, initialEstimate) + isam.update(graph, initialEstimate) result = isam.calculateEstimate() - ISAM2_plot(result) + plot.plot_incremental_trajectory(0, result, + start=i, scale=3, time_interval=0.01) # reset - newgraph = NonlinearFactorGraph() + graph = NonlinearFactorGraph() initialEstimate.clear() + plt.show() + if __name__ == '__main__': IMU_example()