make code match comments when creating Pose3 noiseModel instances
parent
b967c60ccd
commit
a99610b77a
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@ -106,7 +106,7 @@ def IMU_example():
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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([0.3, 0.3, 0.3, 0.1, 0.1, 0.1]))
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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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# Add imu priors
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@ -120,7 +120,7 @@ def visual_ISAM2_example():
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if i == 0:
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# Add a prior on pose x0
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pose_noise = gtsam.noiseModel_Diagonal.Sigmas(np.array(
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[0.3, 0.3, 0.3, 0.1, 0.1, 0.1])) # 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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[0.1, 0.1, 0.1, 0.3, 0.3, 0.3])) # 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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graph.push_back(gtsam.PriorFactorPose3(X(0), poses[0], pose_noise))
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# Add a prior on landmark l0
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@ -27,7 +27,7 @@ int main(int argc, char* argv[]) {
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noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
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Vector6 sigmas;
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sigmas << Vector3::Constant(0.3), Vector3::Constant(0.1);
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sigmas << Vector3::Constant(0.1), Vector3::Constant(0.3);
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auto noise = noiseModel::Diagonal::Sigmas(sigmas);
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ISAM2Params parameters;
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@ -74,7 +74,7 @@ int main(int argc, char* argv[]) {
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NonlinearFactorGraph graph;
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// Add a prior on pose x1. This indirectly specifies where the origin is.
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noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas((Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished()); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas((Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3)).finished()); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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graph.emplace_shared<PriorFactor<Pose3> >(Symbol('x', 0), poses[0], poseNoise); // add directly to graph
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// Simulated measurements from each camera pose, adding them to the factor graph
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@ -81,7 +81,7 @@ int main(int argc, char* argv[]) {
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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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noiseModel::Diagonal::shared_ptr noise = noiseModel::Diagonal::Sigmas(
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(Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished());
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(Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3)).finished());
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graph.emplace_shared<PriorFactor<Pose3> >(0, poses[0], noise);
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// Because the structure-from-motion problem has a scale ambiguity, the problem is
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@ -73,7 +73,7 @@ int main(int argc, char* argv[]) {
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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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noiseModel::Diagonal::shared_ptr noise = noiseModel::Diagonal::Sigmas(
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(Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished());
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(Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3)).finished());
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graph.emplace_shared<PriorFactor<Pose3> >(0, poses[0], noise);
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// Fix the scale ambiguity by adding a prior
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@ -53,7 +53,7 @@ int main(int argc, char* argv[]) {
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NonlinearFactorGraph graph;
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// Add a prior on pose x1.
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noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas((Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished()); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas((Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3)).finished()); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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graph.emplace_shared<PriorFactor<Pose3> >(Symbol('x', 0), poses[0], poseNoise);
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// Simulated measurements from each camera pose, adding them to the factor graph
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@ -108,7 +108,7 @@ int main(int argc, char* argv[]) {
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if (i == 0) {
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// Add a prior on pose x0, 30cm std on x,y,z and 0.1 rad on roll,pitch,yaw
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static auto kPosePrior = noiseModel::Diagonal::Sigmas(
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(Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1))
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(Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3))
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.finished());
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graph.emplace_shared<PriorFactor<Pose3> >(Symbol('x', 0), poses[0],
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kPosePrior);
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@ -107,7 +107,7 @@ int main(int argc, char* argv[]) {
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if (i == 0) {
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// Add a prior on pose x0, with 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas(
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(Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1)).finished());
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(Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3)).finished());
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graph.emplace_shared<PriorFactor<Pose3> >(Symbol('x', 0), poses[0], poseNoise);
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// Add a prior on landmark l0
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@ -25,12 +25,12 @@ graph = NonlinearFactorGraph;
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%% Add a Gaussian prior on pose x_1
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priorMean = Pose3();%Pose3.Expmap([0.0; 0.0; 0.0; 0.0; 0.0; 0.0]); % prior mean is at origin
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priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.3; 0.1; 0.1; 0.1]); % 30cm std on x,y, 0.1 rad on theta
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priorNoise = noiseModel.Diagonal.Sigmas([0.1; 0.1; 0.1; 0.3; 0.3; 0.3]); % 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
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graph.add(PriorFactorPose3(1, priorMean, priorNoise)); % add directly to graph
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%% Add two odometry factors
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odometry = Pose3.Expmap([0.0; 0.0; 0.0; 2.0; 0.0; 0.0]); % create a measurement for both factors (the same in this case)
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odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.2; 0.1; 0.1; 0.1]); % 20cm std on x,y, 0.1 rad on theta
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odometryNoise = noiseModel.Diagonal.Sigmas([0.1; 0.1; 0.1; 0.2; 0.2; 0.2]); % 20cm std on x,y,z 0.1 rad on roll,pitch,yaw
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graph.add(BetweenFactorPose3(1, 2, odometry, odometryNoise));
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graph.add(BetweenFactorPose3(2, 3, odometry, odometryNoise));
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@ -76,7 +76,7 @@ TEST(testVisualISAM2, all)
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{
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// Add a prior on pose x0, 30cm std on x,y,z and 0.1 rad on roll,pitch,yaw
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static auto kPosePrior = noiseModel::Diagonal::Sigmas(
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(Vector(6) << Vector3::Constant(0.3), Vector3::Constant(0.1))
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(Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3))
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.finished());
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graph.emplace_shared<PriorFactor<Pose3>>(Symbol('x', 0), poses[0],
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kPosePrior);
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