| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2022 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
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| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
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| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| namespace ceres { | |
| // In sensor fusion problems, often we have to model quantities that live in | |
| // spaces known as Manifolds, for example the rotation/orientation of a sensor | |
| // that is represented by a quaternion. | |
| // | |
| // Manifolds are spaces which locally look like Euclidean spaces. More | |
| // precisely, at each point on the manifold there is a linear space that is | |
| // tangent to the manifold. It has dimension equal to the intrinsic dimension of | |
| // the manifold itself, which is less than or equal to the ambient space in | |
| // which the manifold is embedded. | |
| // | |
| // For example, the tangent space to a point on a sphere in three dimensions is | |
| // the two dimensional plane that is tangent to the sphere at that point. There | |
| // are two reasons tangent spaces are interesting: | |
| // | |
| // 1. They are Eucliean spaces so the usual vector space operations apply there, | |
| // which makes numerical operations easy. | |
| // 2. Movement in the tangent space translate into movements along the manifold. | |
| // Movements perpendicular to the tangent space do not translate into | |
| // movements on the manifold. | |
| // | |
| // Returning to our sphere example, moving in the 2 dimensional plane | |
| // tangent to the sphere and projecting back onto the sphere will move you away | |
| // from the point you started from but moving along the normal at the same point | |
| // and the projecting back onto the sphere brings you back to the point. | |
| // | |
| // The Manifold interface defines two operations (and their derivatives) | |
| // involving the tangent space, allowing filtering and optimization to be | |
| // performed on said manifold: | |
| // | |
| // 1. x_plus_delta = Plus(x, delta) | |
| // 2. delta = Minus(x_plus_delta, x) | |
| // | |
| // "Plus" computes the result of moving along delta in the tangent space at x, | |
| // and then projecting back onto the manifold that x belongs to. In Differential | |
| // Geometry this is known as a "Retraction". It is a generalization of vector | |
| // addition in Euclidean spaces. | |
| // | |
| // Given two points on the manifold, "Minus" computes the change delta to x in | |
| // the tangent space at x, that will take it to x_plus_delta. | |
| // | |
| // Let us now consider two examples. | |
| // | |
| // The Euclidean space R^n is the simplest example of a manifold. It has | |
| // dimension n (and so does its tangent space) and Plus and Minus are the | |
| // familiar vector sum and difference operations. | |
| // | |
| // Plus(x, delta) = x + delta = y, | |
| // Minus(y, x) = y - x = delta. | |
| // | |
| // A more interesting case is SO(3), the special orthogonal group in three | |
| // dimensions - the space of 3x3 rotation matrices. SO(3) is a three dimensional | |
| // manifold embedded in R^9 or R^(3x3). So points on SO(3) are represented using | |
| // 9 dimensional vectors or 3x3 matrices, and points in its tangent spaces are | |
| // represented by 3 dimensional vectors. | |
| // | |
| // Defining Plus and Minus are defined in terms of the matrix Exp and Log | |
| // operations as follows: | |
| // | |
| // Let Exp(p, q, r) = [cos(theta) + cp^2, -sr + cpq , sq + cpr ] | |
| // [sr + cpq , cos(theta) + cq^2, -sp + cqr ] | |
| // [-sq + cpr , sp + cqr , cos(theta) + cr^2] | |
| // | |
| // where: theta = sqrt(p^2 + q^2 + r^2) | |
| // s = sinc(theta) | |
| // c = (1 - cos(theta))/theta^2 | |
| // | |
| // and Log(x) = 1/(2 sinc(theta))[x_32 - x_23, x_13 - x_31, x_21 - x_12] | |
| // | |
| // where: theta = acos((Trace(x) - 1)/2) | |
| // | |
| // Then, | |
| // | |
| // Plus(x, delta) = x Exp(delta) | |
| // Minus(y, x) = Log(x^T y) | |
| // | |
| // For Plus and Minus to be mathematically consistent, the following identities | |
| // must be satisfied at all points x on the manifold: | |
| // | |
| // 1. Plus(x, 0) = x. | |
| // 2. For all y, Plus(x, Minus(y, x)) = y. | |
| // 3. For all delta, Minus(Plus(x, delta), x) = delta. | |
| // 4. For all delta_1, delta_2 | |
| // |Minus(Plus(x, delta_1), Plus(x, delta_2)) <= |delta_1 - delta_2| | |
| // | |
| // Briefly: | |
| // (1) Ensures that the tangent space is "centered" at x, and the zero vector is | |
| // the identity element. | |
| // (2) Ensures that any y can be reached from x. | |
| // (3) Ensures that Plus is an injective (one-to-one) map. | |
| // (4) Allows us to define a metric on the manifold. | |
| // | |
| // Additionally we require that Plus and Minus be sufficiently smooth. In | |
| // particular they need to be differentiable everywhere on the manifold. | |
| // | |
| // For more details, please see | |
| // | |
| // "Integrating Generic Sensor Fusion Algorithms with Sound State | |
| // Representations through Encapsulation of Manifolds" | |
| // By C. Hertzberg, R. Wagner, U. Frese and L. Schroder | |
| // https://arxiv.org/pdf/1107.1119.pdf | |
| class CERES_EXPORT Manifold { | |
| public: | |
| virtual ~Manifold(); | |
| // Dimension of the ambient space in which the manifold is embedded. | |
| virtual int AmbientSize() const = 0; | |
| // Dimension of the manifold/tangent space. | |
| virtual int TangentSize() const = 0; | |
| // x_plus_delta = Plus(x, delta), | |
| // | |
| // A generalization of vector addition in Euclidean space, Plus computes the | |
| // result of moving along delta in the tangent space at x, and then projecting | |
| // back onto the manifold that x belongs to. | |
| // | |
| // x and x_plus_delta are AmbientSize() vectors. | |
| // delta is a TangentSize() vector. | |
| // | |
| // Return value indicates if the operation was successful or not. | |
| virtual bool Plus(const double* x, | |
| const double* delta, | |
| double* x_plus_delta) const = 0; | |
| // Compute the derivative of Plus(x, delta) w.r.t delta at delta = 0, i.e. | |
| // | |
| // (D_2 Plus)(x, 0) | |
| // | |
| // jacobian is a row-major AmbientSize() x TangentSize() matrix. | |
| // | |
| // Return value indicates whether the operation was successful or not. | |
| virtual bool PlusJacobian(const double* x, double* jacobian) const = 0; | |
| // tangent_matrix = ambient_matrix * (D_2 Plus)(x, 0) | |
| // | |
| // ambient_matrix is a row-major num_rows x AmbientSize() matrix. | |
| // tangent_matrix is a row-major num_rows x TangentSize() matrix. | |
| // | |
| // Return value indicates whether the operation was successful or not. | |
| // | |
| // This function is only used by the GradientProblemSolver, where the | |
| // dimension of the parameter block can be large and it may be more efficient | |
| // to compute this product directly rather than first evaluating the Jacobian | |
| // into a matrix and then doing a matrix vector product. | |
| // | |
| // Because this is not an often used function, we provide a default | |
| // implementation for convenience. If performance becomes an issue then the | |
| // user should consider implementing a specialization. | |
| virtual bool RightMultiplyByPlusJacobian(const double* x, | |
| const int num_rows, | |
| const double* ambient_matrix, | |
| double* tangent_matrix) const; | |
| // y_minus_x = Minus(y, x) | |
| // | |
| // Given two points on the manifold, Minus computes the change to x in the | |
| // tangent space at x, that will take it to y. | |
| // | |
| // x and y are AmbientSize() vectors. | |
| // y_minus_x is a TangentSize() vector. | |
| // | |
| // Return value indicates if the operation was successful or not. | |
| virtual bool Minus(const double* y, | |
| const double* x, | |
| double* y_minus_x) const = 0; | |
| // Compute the derivative of Minus(y, x) w.r.t y at y = x, i.e | |
| // | |
| // (D_1 Minus) (x, x) | |
| // | |
| // Jacobian is a row-major TangentSize() x AmbientSize() matrix. | |
| // | |
| // Return value indicates whether the operation was successful or not. | |
| virtual bool MinusJacobian(const double* x, double* jacobian) const = 0; | |
| }; | |
| // The Euclidean manifold is another name for the ordinary vector space R^size, | |
| // where the plus and minus operations are the usual vector addition and | |
| // subtraction: | |
| // Plus(x, delta) = x + delta | |
| // Minus(y, x) = y - x. | |
| // | |
| // The class works with dynamic and static ambient space dimensions. If the | |
| // ambient space dimensions is know at compile time use | |
| // | |
| // EuclideanManifold<3> manifold; | |
| // | |
| // If the ambient space dimensions is not known at compile time the template | |
| // parameter needs to be set to ceres::DYNAMIC and the actual dimension needs | |
| // to be provided as a constructor argument: | |
| // | |
| // EuclideanManifold<ceres::DYNAMIC> manifold(ambient_dim); | |
| template <int Size> | |
| class EuclideanManifold final : public Manifold { | |
| public: | |
| static_assert(Size == ceres::DYNAMIC || Size >= 0, | |
| "The size of the manifold needs to be non-negative."); | |
| static_assert(ceres::DYNAMIC == Eigen::Dynamic, | |
| "ceres::DYNAMIC needs to be the same as Eigen::Dynamic."); | |
| EuclideanManifold() : size_{Size} { | |
| static_assert( | |
| Size != ceres::DYNAMIC, | |
| "The size is set to dynamic. Please call the constructor with a size."); | |
| } | |
| explicit EuclideanManifold(int size) : size_(size) { | |
| if (Size != ceres::DYNAMIC) { | |
| CHECK_EQ(Size, size) | |
| << "Specified size by template parameter differs from the supplied " | |
| "one."; | |
| } else { | |
| CHECK_GE(size_, 0) | |
| << "The size of the manifold needs to be non-negative."; | |
| } | |
| } | |
| int AmbientSize() const override { return size_; } | |
| int TangentSize() const override { return size_; } | |
| bool Plus(const double* x_ptr, | |
| const double* delta_ptr, | |
| double* x_plus_delta_ptr) const override { | |
| Eigen::Map<const AmbientVector> x(x_ptr, size_); | |
| Eigen::Map<const AmbientVector> delta(delta_ptr, size_); | |
| Eigen::Map<AmbientVector> x_plus_delta(x_plus_delta_ptr, size_); | |
| x_plus_delta = x + delta; | |
| return true; | |
| } | |
| bool PlusJacobian(const double* x_ptr, double* jacobian_ptr) const override { | |
| Eigen::Map<MatrixJacobian> jacobian(jacobian_ptr, size_, size_); | |
| jacobian.setIdentity(); | |
| return true; | |
| } | |
| bool RightMultiplyByPlusJacobian(const double* x, | |
| const int num_rows, | |
| const double* ambient_matrix, | |
| double* tangent_matrix) const override { | |
| std::copy_n(ambient_matrix, num_rows * size_, tangent_matrix); | |
| return true; | |
| } | |
| bool Minus(const double* y_ptr, | |
| const double* x_ptr, | |
| double* y_minus_x_ptr) const override { | |
| Eigen::Map<const AmbientVector> x(x_ptr, size_); | |
| Eigen::Map<const AmbientVector> y(y_ptr, size_); | |
| Eigen::Map<AmbientVector> y_minus_x(y_minus_x_ptr, size_); | |
| y_minus_x = y - x; | |
| return true; | |
| } | |
| bool MinusJacobian(const double* x_ptr, double* jacobian_ptr) const override { | |
| Eigen::Map<MatrixJacobian> jacobian(jacobian_ptr, size_, size_); | |
| jacobian.setIdentity(); | |
| return true; | |
| } | |
| private: | |
| static constexpr bool IsDynamic = (Size == ceres::DYNAMIC); | |
| using AmbientVector = Eigen::Matrix<double, Size, 1>; | |
| using MatrixJacobian = Eigen::Matrix<double, Size, Size, Eigen::RowMajor>; | |
| int size_{}; | |
| }; | |
| // Hold a subset of the parameters inside a parameter block constant. | |
| class CERES_EXPORT SubsetManifold final : public Manifold { | |
| public: | |
| SubsetManifold(int size, const std::vector<int>& constant_parameters); | |
| int AmbientSize() const override; | |
| int TangentSize() const override; | |
| bool Plus(const double* x, | |
| const double* delta, | |
| double* x_plus_delta) const override; | |
| bool PlusJacobian(const double* x, double* jacobian) const override; | |
| bool RightMultiplyByPlusJacobian(const double* x, | |
| const int num_rows, | |
| const double* ambient_matrix, | |
| double* tangent_matrix) const override; | |
| bool Minus(const double* y, | |
| const double* x, | |
| double* y_minus_x) const override; | |
| bool MinusJacobian(const double* x, double* jacobian) const override; | |
| private: | |
| const int tangent_size_ = 0; | |
| std::vector<bool> constancy_mask_; | |
| }; | |
| // Implements the manifold for a Hamilton quaternion as defined in | |
| // https://en.wikipedia.org/wiki/Quaternion. Quaternions are represented as | |
| // unit norm 4-vectors, i.e. | |
| // | |
| // q = [q0; q1; q2; q3], |q| = 1 | |
| // | |
| // is the ambient space representation. | |
| // | |
| // q0 scalar part. | |
| // q1 coefficient of i. | |
| // q2 coefficient of j. | |
| // q3 coefficient of k. | |
| // | |
| // where: i*i = j*j = k*k = -1 and i*j = k, j*k = i, k*i = j. | |
| // | |
| // The tangent space is R^3, which relates to the ambient space through the | |
| // Plus and Minus operations defined as: | |
| // | |
| // Plus(x, delta) = [cos(|delta|); sin(|delta|) * delta / |delta|] * x | |
| // Minus(y, x) = to_delta(y * x^{-1}) | |
| // | |
| // where "*" is the quaternion product and because q is a unit quaternion | |
| // (|q|=1), q^-1 = [q0; -q1; -q2; -q3] | |
| // | |
| // and to_delta( [q0; u_{3x1}] ) = u / |u| * atan2(|u|, q0) | |
| class CERES_EXPORT QuaternionManifold final : public Manifold { | |
| public: | |
| int AmbientSize() const override { return 4; } | |
| int TangentSize() const override { return 3; } | |
| bool Plus(const double* x, | |
| const double* delta, | |
| double* x_plus_delta) const override; | |
| bool PlusJacobian(const double* x, double* jacobian) const override; | |
| bool Minus(const double* y, | |
| const double* x, | |
| double* y_minus_x) const override; | |
| bool MinusJacobian(const double* x, double* jacobian) const override; | |
| }; | |
| // Implements the quaternion manifold for Eigen's representation of the | |
| // Hamilton quaternion. Geometrically it is exactly the same as the | |
| // QuaternionManifold defined above. However, Eigen uses a different internal | |
| // memory layout for the elements of the quaternion than what is commonly | |
| // used. It stores the quaternion in memory as [q1, q2, q3, q0] or | |
| // [x, y, z, w] where the real (scalar) part is last. | |
| // | |
| // Since Ceres operates on parameter blocks which are raw double pointers this | |
| // difference is important and requires a different manifold. | |
| class CERES_EXPORT EigenQuaternionManifold final : public Manifold { | |
| public: | |
| int AmbientSize() const override { return 4; } | |
| int TangentSize() const override { return 3; } | |
| bool Plus(const double* x, | |
| const double* delta, | |
| double* x_plus_delta) const override; | |
| bool PlusJacobian(const double* x, double* jacobian) const override; | |
| bool Minus(const double* y, | |
| const double* x, | |
| double* y_minus_x) const override; | |
| bool MinusJacobian(const double* x, double* jacobian) const override; | |
| }; | |
| } // namespace ceres | |
| // clang-format off | |
| // clang-format on | |