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release/4.3a0
lcarlone 2021-04-03 17:37:36 -04:00
parent 038c1c0b8e
commit 71c528a87d
1 changed files with 115 additions and 97 deletions
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212
gtsam_unstable/slam/SmartStereoProjectionFactorPP.h
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@ -11,7 +11,7 @@
/**
* @file SmartStereoProjectionFactorPP.h
* @brief Smart stereo factor on poses and extrinsic calibration
* @brief Smart stereo factor on poses (P) and camera extrinsic pose (P) calibrations
* @author Luca Carlone
* @author Frank Dellaert
*/
@ -33,8 +33,8 @@ namespace gtsam {
*/
/**
* This factor optimizes the extrinsic camera calibration (pose of camera wrt body),
* and each camera has its own extrinsic calibration.
* This factor optimizes the pose of the body as well as the extrinsic camera calibration (pose of camera wrt body).
* Each camera has its own extrinsic calibration.
* This factor requires that values contain the involved poses and extrinsics (both Pose3).
* @addtogroup SLAM
*/
@ -61,20 +61,20 @@ class SmartStereoProjectionFactorPP : public SmartStereoProjectionFactor {
/// shorthand for a smart pointer to a factor
typedef boost::shared_ptr<This> shared_ptr;
static const int Dim = 12; ///< Camera dimension
static const int DimPose = 6; ///< Camera dimension
static const int ZDim = 3; ///< Measurement dimension
typedef Eigen::Matrix<double, ZDim, Dim> MatrixZD; // F blocks (derivatives wrpt camera)
typedef std::vector<MatrixZD, Eigen::aligned_allocator<MatrixZD> > FBlocks; // vector of F blocks
static const int Dim = 12; ///< Camera dimension
static const int DimPose = 6; ///< Camera dimension
static const int ZDim = 3; ///< Measurement dimension
typedef Eigen::Matrix<double, ZDim, Dim> MatrixZD; // F blocks (derivatives wrpt camera)
typedef std::vector<MatrixZD, Eigen::aligned_allocator<MatrixZD> > FBlocks; // vector of F blocks
/**
* Constructor
* @param Isotropic measurement noise
* @param params internal parameters of the smart factors
*/
SmartStereoProjectionFactorPP(
const SharedNoiseModel& sharedNoiseModel,
const SmartStereoProjectionParams& params = SmartStereoProjectionParams());
SmartStereoProjectionFactorPP(const SharedNoiseModel& sharedNoiseModel,
const SmartStereoProjectionParams& params =
SmartStereoProjectionParams());
/** Virtual destructor */
~SmartStereoProjectionFactorPP() override = default;
@ -87,8 +87,8 @@ class SmartStereoProjectionFactorPP : public SmartStereoProjectionFactor {
* @param body_P_cam_key is key corresponding to the camera observing the same landmark
* @param K is the (fixed) camera calibration
*/
void add(const StereoPoint2& measured,
const Key& w_P_body_key, const Key& body_P_cam_key,
void add(const StereoPoint2& measured, const Key& w_P_body_key,
const Key& body_P_cam_key,
const boost::shared_ptr<Cal3_S2Stereo>& K);
/**
@ -122,13 +122,16 @@ class SmartStereoProjectionFactorPP : public SmartStereoProjectionFactor {
* @param keyFormatter optional formatter useful for printing Symbols
*/
void print(const std::string& s = "", const KeyFormatter& keyFormatter =
DefaultKeyFormatter) const override;
DefaultKeyFormatter) const override;
/// equals
bool equals(const NonlinearFactor& p, double tol = 1e-9) const override;
/// equals
const KeyVector& getExtrinsicPoseKeys() const {return body_P_cam_keys_;};
const KeyVector& getExtrinsicPoseKeys() const {
return body_P_cam_keys_;
}
;
/**
* error calculates the error of the factor.
@ -153,64 +156,67 @@ class SmartStereoProjectionFactorPP : public SmartStereoProjectionFactor {
/// Assumes the point has been computed
/// Note E can be 2m*3 or 2m*2, in case point is degenerate
void computeJacobiansAndCorrectForMissingMeasurements(
FBlocks& Fs,
Matrix& E, Vector& b, const Values& values) const {
FBlocks& Fs, Matrix& E, Vector& b, const Values& values) const {
if (!result_) {
throw ("computeJacobiansWithTriangulatedPoint");
} else { // valid result: compute jacobians
throw("computeJacobiansWithTriangulatedPoint");
} else { // valid result: compute jacobians
size_t numViews = measured_.size();
E = Matrix::Zero(3*numViews,3); // a StereoPoint2 for each view
b = Vector::Zero(3*numViews); // a StereoPoint2 for each view
Matrix dPoseCam_dPoseBody,dPoseCam_dPoseExt, dProject_dPoseCam,Ei;
E = Matrix::Zero(3 * numViews, 3); // a StereoPoint2 for each view
b = Vector::Zero(3 * numViews); // a StereoPoint2 for each view
Matrix dPoseCam_dPoseBody, dPoseCam_dPoseExt, dProject_dPoseCam, Ei;
for (size_t i = 0; i < numViews; i++) { // for each camera/measurement
for (size_t i = 0; i < numViews; i++) { // for each camera/measurement
Pose3 w_P_body = values.at<Pose3>(w_P_body_keys_.at(i));
Pose3 body_P_cam = values.at<Pose3>(body_P_cam_keys_.at(i));
StereoCamera camera(w_P_body.compose(body_P_cam, dPoseCam_dPoseBody, dPoseCam_dPoseExt), K_all_[i]);
StereoPoint2 reprojectionError = StereoPoint2(camera.project(*result_, dProject_dPoseCam, Ei) - measured_.at(i));
Eigen::Matrix<double, ZDim, Dim> J; // 3 x 12
J.block<ZDim,6>(0,0) = dProject_dPoseCam * dPoseCam_dPoseBody; // (3x6) * (6x6)
J.block<ZDim,6>(0,6) = dProject_dPoseCam * dPoseCam_dPoseExt; // (3x6) * (6x6)
if(std::isnan(measured_.at(i).uR())) // if the right pixel is invalid
{
J.block<1,12>(1,0) = Matrix::Zero(1,12);
Ei.block<1,3>(1,0) = Matrix::Zero(1,3);
reprojectionError = StereoPoint2(reprojectionError.uL(), 0.0, reprojectionError.v() );
StereoCamera camera(
w_P_body.compose(body_P_cam, dPoseCam_dPoseBody, dPoseCam_dPoseExt),
K_all_[i]);
StereoPoint2 reprojectionError = StereoPoint2(
camera.project(*result_, dProject_dPoseCam, Ei) - measured_.at(i));
Eigen::Matrix<double, ZDim, Dim> J; // 3 x 12
J.block<ZDim, 6>(0, 0) = dProject_dPoseCam * dPoseCam_dPoseBody; // (3x6) * (6x6)
J.block<ZDim, 6>(0, 6) = dProject_dPoseCam * dPoseCam_dPoseExt; // (3x6) * (6x6)
if (std::isnan(measured_.at(i).uR())) // if the right pixel is invalid
{
J.block<1, 12>(1, 0) = Matrix::Zero(1, 12);
Ei.block<1, 3>(1, 0) = Matrix::Zero(1, 3);
reprojectionError = StereoPoint2(reprojectionError.uL(), 0.0,
reprojectionError.v());
}
Fs.push_back(J);
size_t row = 3*i;
b.segment<ZDim>(row) = - reprojectionError.vector();
E.block<3,3>(row,0) = Ei;
size_t row = 3 * i;
b.segment<ZDim>(row) = -reprojectionError.vector();
E.block<3, 3>(row, 0) = Ei;
}
}
}
/// linearize returns a Hessianfactor that is an approximation of error(p)
boost::shared_ptr<RegularHessianFactor<DimPose> > createHessianFactor(
const Values& values, const double lambda = 0.0, bool diagonalDamping =
const Values& values, const double lambda = 0.0, bool diagonalDamping =
false) const {
size_t nrUniqueKeys = keys_.size();
// Create structures for Hessian Factors
KeyVector js;
std::vector<Matrix> Gs(nrUniqueKeys * (nrUniqueKeys + 1) / 2);
std::vector < Matrix > Gs(nrUniqueKeys * (nrUniqueKeys + 1) / 2);
std::vector<Vector> gs(nrUniqueKeys);
if (this->measured_.size() != cameras(values).size())
throw std::runtime_error("SmartStereoProjectionHessianFactor: this->"
"measured_.size() inconsistent with input");
"measured_.size() inconsistent with input");
triangulateSafe(cameras(values));
if (!result_) {
// failed: return"empty" Hessian
for(Matrix& m: Gs)
m = Matrix::Zero(DimPose,DimPose);
for(Vector& v: gs)
for (Matrix& m : Gs)
m = Matrix::Zero(DimPose, DimPose);
for (Vector& v : gs)
v = Vector::Zero(DimPose);
return boost::make_shared<RegularHessianFactor<DimPose> >(keys_,
Gs, gs, 0.0);
return boost::make_shared < RegularHessianFactor<DimPose>
> (keys_, Gs, gs, 0.0);
}
// Jacobian could be 3D Point3 OR 2D Unit3, difference is E.cols().
@ -229,107 +235,119 @@ class SmartStereoProjectionFactorPP : public SmartStereoProjectionFactor {
Cameras::ComputePointCovariance<3>(P, E, lambda, diagonalDamping);
// marginalize point
SymmetricBlockMatrix augmentedHessian = //
Cameras::SchurComplement<3,Dim>(Fs, E, P, b);
SymmetricBlockMatrix augmentedHessian = //
Cameras::SchurComplement<3, Dim>(Fs, E, P, b);
// now pack into an Hessian factor
std::vector<DenseIndex> dims(nrUniqueKeys + 1); // this also includes the b term
std::vector<DenseIndex> dims(nrUniqueKeys + 1); // this also includes the b term
std::fill(dims.begin(), dims.end() - 1, 6);
dims.back() = 1;
size_t nrNonuniqueKeys = w_P_body_keys_.size() + body_P_cam_keys_.size();
SymmetricBlockMatrix augmentedHessianUniqueKeys;
if ( nrUniqueKeys == nrNonuniqueKeys ){ // if there is 1 calibration key per camera
augmentedHessianUniqueKeys = SymmetricBlockMatrix(dims, Matrix(augmentedHessian.selfadjointView()));
}else{ // if multiple cameras share a calibration
std::vector<DenseIndex> nonuniqueDims(nrNonuniqueKeys + 1); // this also includes the b term
if (nrUniqueKeys == nrNonuniqueKeys) { // if there is 1 calibration key per camera
augmentedHessianUniqueKeys = SymmetricBlockMatrix(
dims, Matrix(augmentedHessian.selfadjointView()));
} else { // if multiple cameras share a calibration
std::vector<DenseIndex> nonuniqueDims(nrNonuniqueKeys + 1); // this also includes the b term
std::fill(nonuniqueDims.begin(), nonuniqueDims.end() - 1, 6);
nonuniqueDims.back() = 1;
augmentedHessian = SymmetricBlockMatrix(nonuniqueDims, Matrix(augmentedHessian.selfadjointView()));
augmentedHessian = SymmetricBlockMatrix(
nonuniqueDims, Matrix(augmentedHessian.selfadjointView()));
// these are the keys that correspond to the blocks in augmentedHessian (output of SchurComplement)
KeyVector nonuniqueKeys;
for(size_t i=0; i < w_P_body_keys_.size();i++){
for (size_t i = 0; i < w_P_body_keys_.size(); i++) {
nonuniqueKeys.push_back(w_P_body_keys_.at(i));
nonuniqueKeys.push_back(body_P_cam_keys_.at(i));
}
// get map from key to location in the new augmented Hessian matrix (the one including only unique keys)
std::map<Key,size_t> keyToSlotMap;
for(size_t k=0; k<nrUniqueKeys;k++){
std::map<Key, size_t> keyToSlotMap;
for (size_t k = 0; k < nrUniqueKeys; k++) {
keyToSlotMap[keys_[k]] = k;
}
// initialize matrix to zero
augmentedHessianUniqueKeys = SymmetricBlockMatrix(dims, Matrix::Zero(6*nrUniqueKeys+1,6*nrUniqueKeys+1));
augmentedHessianUniqueKeys = SymmetricBlockMatrix(
dims, Matrix::Zero(6 * nrUniqueKeys + 1, 6 * nrUniqueKeys + 1));
// add contributions for each key: note this loops over the hessian with nonUnique keys (augmentedHessian)
for(size_t i=0; i<nrNonuniqueKeys;i++){ // rows
for (size_t i = 0; i < nrNonuniqueKeys; i++) { // rows
Key key_i = nonuniqueKeys.at(i);
// update information vector
augmentedHessianUniqueKeys.updateOffDiagonalBlock( keyToSlotMap[key_i] , nrUniqueKeys,
augmentedHessian.aboveDiagonalBlock(i,nrNonuniqueKeys));
augmentedHessianUniqueKeys.updateOffDiagonalBlock(
keyToSlotMap[key_i], nrUniqueKeys,
augmentedHessian.aboveDiagonalBlock(i, nrNonuniqueKeys));
// update blocks
for(size_t j=i; j<nrNonuniqueKeys;j++){ // cols
for (size_t j = i; j < nrNonuniqueKeys; j++) { // cols
Key key_j = nonuniqueKeys.at(j);
if(i==j){
augmentedHessianUniqueKeys.updateDiagonalBlock( keyToSlotMap[key_i] , augmentedHessian.diagonalBlock(i));
}else{ // (i < j)
if( keyToSlotMap[key_i] != keyToSlotMap[key_j] ){
augmentedHessianUniqueKeys.updateOffDiagonalBlock( keyToSlotMap[key_i] , keyToSlotMap[key_j],
augmentedHessian.aboveDiagonalBlock(i,j));
}else{
augmentedHessianUniqueKeys.updateDiagonalBlock( keyToSlotMap[key_i] ,
augmentedHessian.aboveDiagonalBlock(i,j) +
augmentedHessian.aboveDiagonalBlock(i,j).transpose());
if (i == j) {
augmentedHessianUniqueKeys.updateDiagonalBlock(
keyToSlotMap[key_i], augmentedHessian.diagonalBlock(i));
} else { // (i < j)
if (keyToSlotMap[key_i] != keyToSlotMap[key_j]) {
augmentedHessianUniqueKeys.updateOffDiagonalBlock(
keyToSlotMap[key_i], keyToSlotMap[key_j],
augmentedHessian.aboveDiagonalBlock(i, j));
} else {
augmentedHessianUniqueKeys.updateDiagonalBlock(
keyToSlotMap[key_i],
augmentedHessian.aboveDiagonalBlock(i, j)
+ augmentedHessian.aboveDiagonalBlock(i, j).transpose());
}
}
}
}
augmentedHessianUniqueKeys.updateDiagonalBlock(nrUniqueKeys, augmentedHessian.diagonalBlock(nrNonuniqueKeys));
augmentedHessianUniqueKeys.updateDiagonalBlock(
nrUniqueKeys, augmentedHessian.diagonalBlock(nrNonuniqueKeys));
}
return boost::make_shared<RegularHessianFactor<DimPose> >(keys_, augmentedHessianUniqueKeys);
return boost::make_shared < RegularHessianFactor<DimPose>
> (keys_, augmentedHessianUniqueKeys);
}
/**
* Linearize to Gaussian Factor
* @param values Values structure which must contain camera poses and extrinsic pose for this factor
* @return a Gaussian factor
*/
boost::shared_ptr<GaussianFactor> linearizeDamped(const Values& values,
const double lambda = 0.0) const {
// depending on flag set on construction we may linearize to different linear factors
switch (params_.linearizationMode) {
case HESSIAN:
return createHessianFactor(values, lambda);
default:
throw std::runtime_error("SmartStereoProjectionFactorPP: unknown linearization mode");
}
}
* Linearize to Gaussian Factor (possibly adding a damping factor Lambda for LM)
* @param values Values structure which must contain camera poses and extrinsic pose for this factor
* @return a Gaussian factor
*/
boost::shared_ptr<GaussianFactor> linearizeDamped(
const Values& values, const double lambda = 0.0) const {
// depending on flag set on construction we may linearize to different linear factors
switch (params_.linearizationMode) {
case HESSIAN:
return createHessianFactor(values, lambda);
default:
throw std::runtime_error(
"SmartStereoProjectionFactorPP: unknown linearization mode");
}
}
/// linearize
boost::shared_ptr<GaussianFactor> linearize(
const Values& values) const override {
return linearizeDamped(values);
}
/// linearize
boost::shared_ptr<GaussianFactor> linearize(const Values& values) const
override {
return linearizeDamped(values);
}
private:
/// Serialization function
friend class boost::serialization::access;
template <class ARCHIVE>
template<class ARCHIVE>
void serialize(ARCHIVE& ar, const unsigned int /*version*/) {
ar& BOOST_SERIALIZATION_BASE_OBJECT_NVP(Base);
ar& BOOST_SERIALIZATION_NVP(K_all_);
ar & BOOST_SERIALIZATION_NVP(K_all_);
}
}; // end of class declaration
};
// end of class declaration
/// traits
template <>
struct traits<SmartStereoProjectionFactorPP>
: public Testable<SmartStereoProjectionFactorPP> {};
template<>
struct traits<SmartStereoProjectionFactorPP> : public Testable<
SmartStereoProjectionFactorPP> {
};
} // namespace gtsam