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/*
 * Copyright (c) 2015, Georgia Tech Research Corporation
 * All rights reserved.
 *
 * Author(s): Michael X. Grey <mxgrey@gatech.edu>
 *
 * Georgia Tech Graphics Lab and Humanoid Robotics Lab
 *
 * Directed by Prof. C. Karen Liu and Prof. Mike Stilman
 * <karenliu@cc.gatech.edu> <mstilman@cc.gatech.edu>
 *
 * This file is provided under the following "BSD-style" License:
 *   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 and/or other materials provided
 *     with the distribution.
 *   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
 *   CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
 *   INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
 *   MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 *   DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
 *   CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
 *   SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
 *   LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
 *   USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
 *   AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
 *   LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
 *   ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 *   POSSIBILITY OF SUCH DAMAGE.
 */

#ifndef KIDO_DYNAMICS_INVERSEKINEMATICS_HPP_
#define KIDO_DYNAMICS_INVERSEKINEMATICS_HPP_

#include <memory>
#include <functional>

#include <Eigen/SVD>

#include "kido/common/sub_ptr.hpp"
#include "kido/common/Signal.hpp"
#include "kido/common/Subject.hpp"
#include "kido/math/Geometry.hpp"
#include "kido/optimizer/Solver.hpp"
#include "kido/optimizer/GradientDescentSolver.hpp"
#include "kido/optimizer/Problem.hpp"
#include "kido/optimizer/Function.hpp"
#include "kido/dynamics/SmartPointer.hpp"
#include "kido/dynamics/JacobianNode.hpp"

namespace kido {
namespace dynamics {

const double DefaultIKTolerance = 1e-6;
const double DefaultIKErrorClamp = 1.0;
const double DefaultIKGradientComponentClamp = 0.2;
const double DefaultIKGradientComponentWeight = 1.0;
const double DefaultIKDLSCoefficient = 0.05;
const double DefaultIKAngularWeight = 0.4;
const double DefaultIKLinearWeight = 1.0;

/// The InverseKinematics class provides a convenient way of setting up an IK
/// optimization problem. It generates constraint functions based on the
/// specified InverseKinematics::ErrorMethod and
/// InverseKinematics::GradientMethod.
///
/// It also provides a convenient way of specifying a configuration space
/// objective and a null space objective. It is also possible to fully customize
/// the optimizer::Problem that the module creates, and the IK module can be
/// safely cloned  over to another JacobianNode, as long as every
/// optimizer::Function that depends on the JacobianNode inherits the
/// InverseKinematics::Function class and correctly overloads the clone function
class InverseKinematics : public common::Subject
{
public:

  /// Create an InverseKinematics module for a specified node
  static InverseKinematicsPtr create(JacobianNode* _node);

  /// Copying is not allowed
  InverseKinematics(const InverseKinematics&) = delete;

  /// Assignment is not allowed
  InverseKinematics& operator = (const InverseKinematics&) = delete;

  /// Virtual destructor
  virtual ~InverseKinematics();

  /// Solve the IK Problem. By default, the Skeleton itself will retain the
  /// solved joint positions. If you pass in false for _applySolution, then the
  /// joint positions will be returned to their original positions after the
  /// problem is solved.
  bool solve(bool _applySolution = true);

  /// Same as solve(bool), but the positions vector will be filled with the
  /// solved positions.
  bool solve(Eigen::VectorXd& positions, bool _applySolution = true);

  /// Clone this IK module, but targeted at a new Node. Any Functions in the
  /// Problem that inherit InverseKinematics::Function will be adapted to the
  /// new IK module. Any generic optimizer::Function will just be copied over
  /// by pointer instead of being cloned.
  InverseKinematicsPtr clone(JacobianNode* _newNode) const;

  /// This class should be inherited by optimizer::Function classes that have a
  /// dependency on the InverseKinematics module that they belong to. If you
  /// pass an InverseKinematics::Function into the Problem of an
  /// InverseKinematics module, then it will be properly cloned whenever the
  /// InverseKinematics module that it belongs to gets cloned. Any Function
  /// classes in the Problem that do not inherit InverseKinematics::Function
  /// will just be copied over by reference.
  class Function
  {
  public:

    /// Enable this function to be cloned to a new IK module.
    virtual optimizer::FunctionPtr clone(InverseKinematics* _newIK) const = 0;

    /// Virtual destructor
    virtual ~Function() = default;
  };

  /// ErrorMethod is a base class for different ways of computing the error of
  /// an InverseKinematics module.
  class ErrorMethod : public common::Subject
  {
  public:

    typedef std::pair<Eigen::Vector6d, Eigen::Vector6d> Bounds;

    /// The Properties struct contains settings that are commonly used by
    /// methods that compute error for inverse kinematics.
    struct Properties
    {
      /// Default constructor
      Properties(const Bounds& _bounds =
            Bounds(Eigen::Vector6d::Constant(-DefaultIKTolerance),
                   Eigen::Vector6d::Constant( DefaultIKTolerance)),

          double _errorClamp = DefaultIKErrorClamp,

          const Eigen::Vector6d& _errorWeights = Eigen::compose(
            Eigen::Vector3d::Constant(DefaultIKAngularWeight),
            Eigen::Vector3d::Constant(DefaultIKLinearWeight)));

      /// Bounds that define the acceptable range of the Node's transform
      /// relative to its target frame.
      std::pair<Eigen::Vector6d, Eigen::Vector6d> mBounds;

      /// The error vector will be clamped to this length with each iteration.
      /// This is used to enforce sane behavior, even when there are extremely
      /// large error vectors.
      double mErrorLengthClamp;

      /// These weights will be applied to the error vector component-wise. This
      /// allows you to set some components of error as more important than
      /// others, or to scale their coordinate spaces. For example, you will
      /// often want the first three components (orientation error) to have
      /// smaller weights than the last three components (translation error).
      Eigen::Vector6d mErrorWeights;

      // To get byte-aligned Eigen vectors
      EIGEN_MAKE_ALIGNED_OPERATOR_NEW
    };

    /// Constructor
    ErrorMethod(InverseKinematics* _ik,
                const std::string& _methodName,
                const Properties& _properties = Properties());

    /// Virtual destructor
    virtual ~ErrorMethod() = default;

    /// Enable this ErrorMethod to be cloned to a new IK module.
    virtual std::unique_ptr<ErrorMethod> clone(
        InverseKinematics* _newIK) const = 0;

    /// Override this function with your implementation of the error vector
    /// computation. The expectation is that the first three components of the
    /// vector will correspond to orientation error (in an angle-axis format)
    /// while the last three components correspond to translational error.
    ///
    /// When implementing this function, you should assume that the Skeleton's
    /// current joint positions corresponds to the positions that you
    /// must use to compute the error. This function will only get called when
    /// an update is needed.
    virtual Eigen::Vector6d computeError() = 0;

    /// Override this function with your implementation of computing the desired
    /// given the current transform and error vector. If you want the desired
    /// transform to always be equal to the Target's transform, you can simply
    /// call ErrorMethod::computeDesiredTransform to implement this function.
    virtual Eigen::Isometry3d computeDesiredTransform(
        const Eigen::Isometry3d& _currentTf, const Eigen::Vector6d& _error) = 0;

    /// This function is used to handle caching the error vector.
    const Eigen::Vector6d& evalError(const Eigen::VectorXd& _q);

    /// Get the name of this ErrorMethod.
    const std::string& getMethodName() const;

    /// Set all the error bounds.
    void setBounds(
        const Eigen::Vector6d& _lower =
            Eigen::Vector6d::Constant(-DefaultIKTolerance),
        const Eigen::Vector6d& _upper =
            Eigen::Vector6d::Constant( DefaultIKTolerance));

    /// Set all the error bounds.
    void setBounds(const std::pair<Eigen::Vector6d, Eigen::Vector6d>& _bounds);

    /// Get all the error bounds.
    const std::pair<Eigen::Vector6d, Eigen::Vector6d>& getBounds() const;

    /// Set the error bounds for orientation.
    void setAngularBounds(
        const Eigen::Vector3d& _lower =
            Eigen::Vector3d::Constant(-DefaultIKTolerance),
        const Eigen::Vector3d& _upper =
            Eigen::Vector3d::Constant( DefaultIKTolerance));

    /// Set the error bounds for orientation.
    void setAngularBounds(
        const std::pair<Eigen::Vector3d, Eigen::Vector3d>& _bounds);

    /// Get the error bounds for orientation.
    std::pair<Eigen::Vector3d, Eigen::Vector3d> getAngularBounds() const;

    /// Set the error bounds for translation.
    void setLinearBounds(
        const Eigen::Vector3d& _lower =
            Eigen::Vector3d::Constant(-DefaultIKTolerance),
        const Eigen::Vector3d& _upper =
            Eigen::Vector3d::Constant( DefaultIKTolerance));

    /// Set the error bounds for translation.
    void setLinearBounds(
        const std::pair<Eigen::Vector3d, Eigen::Vector3d>& _bounds);

    /// Get the error bounds for translation.
    std::pair<Eigen::Vector3d, Eigen::Vector3d> getLinearBounds() const;

    /// Set the clamp that will be applied to the length of the error vector
    /// each iteration.
    void setErrorLengthClamp(double _clampSize = DefaultIKErrorClamp);

    /// Set the clamp that will be applied to the length of the error vector
    /// each iteration.
    double getErrorLengthClamp() const;

    /// Set the weights that will be applied to each component of the error
    /// vector.
    void setErrorWeights(const Eigen::Vector6d& _weights);

    /// Get the weights that will be applied to each component of the error
    /// vector.
    const Eigen::Vector6d& getErrorWeights() const;

    /// Set the weights that will be applied to each angular component of the
    /// error vector.
    void setAngularErrorWeights(
        const Eigen::Vector3d& _weights =
          Eigen::Vector3d::Constant(DefaultIKAngularWeight));

    /// Get the weights that will be applied to each angular component of the
    /// error vector.
    Eigen::Vector3d getAngularErrorWeights() const;

    /// Set the weights that will be applied to each linear component of the
    /// error vector.
    void setLinearErrorWeights(
        const Eigen::Vector3d& _weights =
          Eigen::Vector3d::Constant(DefaultIKLinearWeight));

    /// Get the weights that will be applied to each linear component of the
    /// error vector.
    Eigen::Vector3d getLinearErrorWeights() const;

    /// Get the Properties of this ErrorMethod
    Properties getErrorMethodProperties() const;

    /// Clear the cache to force the error to be recomputed. It should generally
    /// not be necessary to call this function.
    void clearCache();

  protected:

    /// Pointer to the IK module of this ErrorMethod
    common::sub_ptr<InverseKinematics> mIK;

    /// Name of this error method
    std::string mMethodName;

    /// The last joint positions passed into this ErrorMethod
    Eigen::VectorXd mLastPositions;

    /// The last error vector computed by this ErrorMethod
    Eigen::Vector6d mLastError;

    /// The properties of this ErrorMethod
    Properties mErrorP;

  public:
    // To get byte-aligned Eigen vectors
    EIGEN_MAKE_ALIGNED_OPERATOR_NEW

  };

  /// The TaskSpaceRegion is a nicely generalized method for computing the error
  /// of an IK Problem.
  class TaskSpaceRegion : public ErrorMethod
  {
  public:

    struct UniqueProperties
    {
      /// Setting this to true (which is default) will tell it to compute the
      /// error based on the center of the Task Space Region instead of the edge
      /// of the Task Space Region. This often results in faster convergence, as
      /// the Node will enter the Task Space Region more aggressively.
      ///
      /// Once the Node is inside the Task Space Region, the error vector will
      /// drop to zero, regardless of whether this flag is true or false.
      bool mComputeErrorFromCenter;

      /// Default constructor
      UniqueProperties(bool computeErrorFromCenter = true);
    };

    struct Properties : ErrorMethod::Properties, UniqueProperties
    {
      /// Default constructor
      Properties(
          const ErrorMethod::Properties& errorProperties =
              ErrorMethod::Properties(),
          const UniqueProperties& taskSpaceProperties = UniqueProperties());
    };

    /// Default Constructor
    explicit TaskSpaceRegion(InverseKinematics* _ik,
                             const Properties& _properties = Properties());

    /// Virtual destructor
    virtual ~TaskSpaceRegion() = default;

    // Documentation inherited
    std::unique_ptr<ErrorMethod> clone(InverseKinematics* _newIK) const override;

    // Documentation inherited
    Eigen::Isometry3d computeDesiredTransform(
        const Eigen::Isometry3d& _currentTf,
        const Eigen::Vector6d& _error) override;

    // Documentation inherited
    Eigen::Vector6d computeError() override;

    /// Set whether this TaskSpaceRegion should compute its error vector from
    /// the center of the region.
    void setComputeFromCenter(bool computeFromCenter);

    /// Get whether this TaskSpaceRegion is set to compute its error vector from
    /// the center of the region.
    bool isComputingFromCenter() const;

    /// Get the Properties of this TaskSpaceRegion
    Properties getTaskSpaceRegionProperties() const;

  protected:

    /// Properties of this TaskSpaceRegion
    UniqueProperties mTaskSpaceP;

  };

  /// GradientMethod is a base class for different ways of computing the
  /// gradient of an InverseKinematics module.
  class GradientMethod : public common::Subject
  {
  public:

    struct Properties
    {
      /// The component-wise clamp for this GradientMethod
      double mComponentWiseClamp;

      /// The weights for this GradientMethod
      Eigen::VectorXd mComponentWeights;

      /// Default constructor
      Properties(double clamp = DefaultIKGradientComponentClamp,
                 const Eigen::VectorXd& weights = Eigen::VectorXd());
    };

    /// Constructor
    GradientMethod(InverseKinematics* _ik,
                   const std::string& _methodName,
                   const Properties& _properties);

    /// Virtual destructor
    virtual ~GradientMethod() = default;

    /// Enable this GradientMethod to be cloned to a new IK module
    virtual std::unique_ptr<GradientMethod> clone(
        InverseKinematics* _newIK) const = 0;

    /// Override this function with your implementation of the gradient
    /// computation. The direction that this gradient points in should make the
    /// error **worse** if applied to the joint positions, because the
    /// Problem is configured as a gradient **descent** error minimization
    /// Problem.
    ///
    /// The error vector that is passed in will be determined by the IK module's
    /// ErrorMethod. The expectation is that the first three components of the
    /// vector correspond to orientation error (in an angle-axis format) while
    /// the last three components correspond to translational error.
    ///
    /// When implementing this function, you should assume that the Skeleton's
    /// current joint positions corresponds to the positions that you
    /// must use to compute the error. This function will only get called when
    /// an update is needed.
    virtual void computeGradient(const Eigen::Vector6d& _error,
                                 Eigen::VectorXd& _grad) = 0;

    /// This function is used to handle caching the gradient vector and
    /// interfacing with the solver.
    void evalGradient(const Eigen::VectorXd& _q,
                      Eigen::Map<Eigen::VectorXd> _grad);

    /// Get the name of this GradientMethod.
    const std::string& getMethodName() const;

    /// Clamp the gradient based on the clamp settings of this GradientMethod.
    void clampGradient(Eigen::VectorXd& _grad) const;

    /// Set the component-wise clamp for this GradientMethod. Each component
    /// of the gradient will be individually clamped to this size.
    void setComponentWiseClamp(double _clamp = DefaultIKGradientComponentClamp);

    /// Get the component-wise clamp for this GradientMethod.
    double getComponentWiseClamp() const;

    /// Apply weights to the gradient based on the weight settings of this
    /// GradientMethod.
    void applyWeights(Eigen::VectorXd& _grad) const;

    /// Set the weights that will be applied to each component of the gradient.
    /// If the number of components in _weights is smaller than the number of
    /// components in the gradient, then a weight of 1.0 will be applied to all
    /// components that are out of the range of _weights. Passing in an empty
    /// vector for _weights will effectively make all the gradient components
    /// unweighted.
    void setComponentWeights(const Eigen::VectorXd& _weights);

    /// Get the weights of this GradientMethod.
    const Eigen::VectorXd& getComponentWeights() const;

    /// Get the Properties of this GradientMethod
    Properties getGradientMethodProperties() const;

    /// Clear the cache to force the gradient to be recomputed. It should
    /// generally not be necessary to call this function.
    void clearCache();

  protected:

    /// The IK module that this GradientMethod belongs to.
    common::sub_ptr<InverseKinematics> mIK;

    /// The name of this method
    std::string mMethodName;

    /// The last positions that was passed to this GradientMethod
    Eigen::VectorXd mLastPositions;

    /// The last gradient that was computed by this GradientMethod
    Eigen::VectorXd mLastGradient;

    /// Properties for this GradientMethod
    Properties mGradientP;

  };

  /// JacobianDLS refers to the Damped Least Squares Jacobian Pseudoinverse
  /// (specifically, Moore-Penrose Pseudoinverse). This is a very precise method
  /// for computing the gradient and is especially suitable for performing IK on
  /// industrial manipulators that need to follow very exact workspace paths.
  /// However, it is vulnerable to be jittery around singularities (though the
  /// damping helps with this), and each cycle might take more time to compute
  /// than the JacobianTranspose method (although the JacobianDLS method will
  /// usually converge in fewer cycles than JacobianTranspose).
  class JacobianDLS : public GradientMethod
  {
  public:

    struct UniqueProperties
    {
      /// Damping coefficient
      double mDamping;

      /// Default constructor
      UniqueProperties(double damping = DefaultIKDLSCoefficient);
    };

    struct Properties : GradientMethod::Properties, UniqueProperties
    {
      /// Default constructor
      Properties(
          const GradientMethod::Properties& gradientProperties =
              GradientMethod::Properties(),
          const UniqueProperties& dlsProperties = UniqueProperties());
    };

    /// Constructor
    explicit JacobianDLS(InverseKinematics* _ik,
                         const Properties& properties = Properties());

    /// Virtual destructor
    virtual ~JacobianDLS() = default;

    // Documentation inherited
    std::unique_ptr<GradientMethod> clone(
        InverseKinematics* _newIK) const override;

    // Documentation inherited
    void computeGradient(const Eigen::Vector6d& _error,
                         Eigen::VectorXd& _grad) override;

    /// Set the damping coefficient. A higher damping coefficient will smooth
    /// out behavior around singularities but will also result in less precision
    /// in general. The default value is appropriate for most use cases.
    void setDampingCoefficient(double _damping = DefaultIKDLSCoefficient);

    /// Get the damping coefficient.
    double getDampingCoefficient() const;

    /// Get the Properties of this JacobianDLS
    Properties getJacobianDLSProperties() const;

  protected:

    /// Properties of this Damped Least Squares method
    UniqueProperties mDLSProperties;

  };

  /// JacobianTranspose will simply apply the transpose of the Jacobian to the
  /// error vector in order to compute the gradient. This method tends to be
  /// very smooth but imprecise, requiring more iterations before converging
  /// and being less precise in general. This method is suitable for animations
  /// where smoothness is prefered over precision.
  class JacobianTranspose : public GradientMethod
  {
  public:

    /// Constructor
    explicit JacobianTranspose(InverseKinematics* _ik,
                               const Properties& properties = Properties());

    /// Virtual destructor
    virtual ~JacobianTranspose() = default;

    // Documentation inherited
    std::unique_ptr<GradientMethod> clone(
        InverseKinematics* _newIK) const override;

    // Documentation inherited
    void computeGradient(const Eigen::Vector6d& _error,
                         Eigen::VectorXd& _grad) override;
  };

  /// Analytical is a base class that should be inherited by methods that are
  /// made to solve the IK analytically instead of iteratively. This provides an
  /// extended API that is relevant to Analytical solvers but not iterative
  /// solvers.
  ///
  /// Creating an Analytical solver will have the side effect of removing the
  /// error clamp and error weights from your ErrorMethod. If you still want
  /// your error computations to be clamped and weighted, you should set it
  /// again after creating the Analytical solver. Clamping and weighting the
  /// error vector often helps iterative methods to converge smoothly, but it is
  /// counter-productive for analytical methods which do not typically rely on
  /// convergence; analytical methods can usually solve the entire error vector
  /// directly.
  class Analytical : public GradientMethod
  {
  public:

    /// Bitwise enumerations that are used to describe some properties of each
    /// solution produced by the analytical IK.
    enum Validity_t
    {
      VALID = 0,                ///< The solution is completely valid and reaches the target
      OUT_OF_REACH   = 1 << 0,  ///< The solution does not reach the target
      LIMIT_VIOLATED = 1 << 1   ///< The solution has one or more joint positions that violate the joint limits
    };

    /// If there are extra DOFs in the IK module which your Analytical solver
    /// implementation does not make use of, those DOFs can be used to
    /// supplement the analytical solver using Jacobian transpose iteration.
    /// This enumeration is used to indicate whether you want those DOFs to be
    /// used before applying the analytical solution, after applying the
    /// analytical solution, or not be used at all.
    ///
    /// Jacobian transpose is used for the extra DOFs because it is inexpensive
    /// and robust to degenerate Jacobians which are common in low dimensional
    /// joint spaces. The primary advantage of pseudoinverse methods over
    /// Jacobian transpose methods is their precision, but analytical methods
    /// are even more precise than pseudoinverse methods, so that precision is
    /// not needed in this case.
    ///
    /// If you want the extra DOFs to use a different method than Jacobian
    /// transpose, you can create two seperate IK modules (one which is
    /// analytical and one with the iterative method of your choice) and combine
    /// them in a HierarchicalIK.
    enum ExtraDofUtilization_t
    {
      UNUSED = 0,
      PRE_ANALYTICAL,
      POST_ANALYTICAL
    };

    struct Solution
    {
      /// Default constructor
      Solution(const Eigen::VectorXd& _config = Eigen::VectorXd(),
               int _validity = VALID);

      /// Configuration computed by the Analytical solver
      Eigen::VectorXd mConfig;

      /// Bitmap for whether this configuration is valid. Bitwise-compare it to
      /// the enumerations in Validity_t to whether this configuration is valid.
      int mValidity;
    };

    // std::function template for comparing the quality of configurations
    typedef std::function<bool(
        const Eigen::VectorXd& _better,
        const Eigen::VectorXd& _worse,
        const InverseKinematics* _ik)> QualityComparison;

    struct UniqueProperties
    {
      /// Flag for how to use the extra DOFs in the IK module.
      ExtraDofUtilization_t mExtraDofUtilization;

      /// How much to clamp the extra error that gets applied to DOFs
      double mExtraErrorLengthClamp;

      /// Function for comparing the qualities of solutions
      QualityComparison mQualityComparator;

      /// Default constructor. Uses a default quality comparison function.
      UniqueProperties(ExtraDofUtilization_t extraDofUtilization = UNUSED,
                 double extraErrorLengthClamp = DefaultIKErrorClamp);

      /// Constructor that allows you to set the quality comparison function.
      UniqueProperties(ExtraDofUtilization_t extraDofUtilization,
                 double extraErrorLengthClamp,
                 QualityComparison qualityComparator);

      /// Reset the quality comparison function to its default behavior.
      void resetQualityComparisonFunction();
    };

    struct Properties : GradientMethod::Properties, UniqueProperties
    {
      // Default constructor
      Properties(
          const GradientMethod::Properties& gradientProperties =
              GradientMethod::Properties(),
          const UniqueProperties& analyticalProperties = UniqueProperties());

      // Construct Properties by specifying the UniqueProperties. The
      // GradientMethod::Properties components will be set to defaults.
      Properties(const UniqueProperties& analyticalProperties);
    };

    /// Constructor
    Analytical(InverseKinematics* _ik, const std::string& _methodName,
               const Properties& _properties);

    /// Virtual destructor
    virtual ~Analytical() = default;

    /// Get the solutions for this IK module, along with a tag indicating
    /// whether each solution is valid. This function will assume that you want
    /// to use the desired transform given by the IK module's current
    /// ErrorMethod.
    const std::vector<Solution>& getSolutions();

    /// Get the solutions for this IK module, along with a tag indicating
    /// whether each solution is valid. This function will compute the
    /// configurations using the given desired transform instead of using the
    /// IK module's current ErrorMethod.
    const std::vector<Solution>& getSolutions(
        const Eigen::Isometry3d& _desiredTf);

    /// You should not need to override this function. Instead, you should
    /// override computeSolutions.
    void computeGradient(const Eigen::Vector6d& _error,
                         Eigen::VectorXd& _grad) override;

    /// Use this function to fill the entries of the mSolutions variable. Be
    /// sure to clear the mSolutions vector at the start, and to also return the
    /// mSolutions vector at the end. Note that you are not expected to evaluate
    /// any of the solutions for their quality. However, you should set the
    /// Solution::mValidity flag to OUT_OF_REACH for each solution that does not
    /// actually reach the desired transform, and you should call
    /// checkSolutionJointLimits() and the end of the function, which will set
    /// the LIMIT_VIOLATED flags of any configurations that are outside of the
    /// position limits.
    virtual const std::vector<Solution>& computeSolutions(
        const Eigen::Isometry3d& _desiredBodyTf) = 0;

    /// Get a list of the DOFs that will be included in the entries of the
    /// solutions returned by getSolutions(). Ideally, this should match up with
    /// the DOFs being used by the InverseKinematics module, but this might not
    /// always be possible, so this function ensures that solutions can be
    /// interpreted correctly.
    virtual const std::vector<size_t>& getDofs() const = 0;

    /// Set the configuration of the DOFs. The components of _config must
    /// correspond to the DOFs provided by getDofs().
    void setPositions(const Eigen::VectorXd& _config);

    /// Get the configuration of the DOFs. The components of this vector will
    /// correspond to the DOFs provided by getDofs().
    Eigen::VectorXd getPositions() const;

    /// Set how you want extra DOFs to be utilized by the IK module
    void setExtraDofUtilization(ExtraDofUtilization_t _utilization);

    /// Get how extra DOFs are being utilized by the IK module
    ExtraDofUtilization_t getExtraDofUtilization() const;

    /// Set how much to clamp the error vector that gets applied to extra DOFs
    void setExtraErrorLengthClamp(double _clamp);

    /// Get how much we will clamp the error vector that gets applied to extra
    /// DOFs
    double getExtraErrorLengthClamp() const;

    /// Set the function that will be used to compare the qualities of two
    /// solutions. This function should return true if the first argument is a
    /// better solution than the second argument.
    ///
    /// By default, it will prefer the solution which has the smallest size for
    /// its largest change in joint angle. In other words, for each
    /// configuration that it is given, it will compare the largest change in
    /// joint angle for each configuration and pick the one that is smallest.
    ///
    /// Note that outside of this comparison function, the Solutions will be
    /// split between which are valid, which are out-of-reach, and which are
    /// in violation of joint limits. Valid solutions will always be ranked
    /// above invalid solutions, and joint limit violations will always be
    /// ranked last.
    void setQualityComparisonFunction(const QualityComparison& _func);

    /// Reset the quality comparison function to the default method.
    void resetQualityComparisonFunction();

    /// Get the Properties for this Analytical class
    Properties getAnalyticalProperties() const;

    /// Construct a mapping from the DOFs of getDofs() to their indices within
    /// the Node's list of dependent DOFs. This will be called immediately after
    /// the Analytical is constructed; this one call is sufficient as long as
    /// the DOFs of Analytical::getDofs() is not changed. However, if your
    /// Analytical is able to change the DOFs that it operates on, then you will
    /// need to call this function each time the DOFs have changed.
    void constructDofMap();

  protected:

    /// Go through the mSolutions vector and tag entries with LIMIT_VIOLATED if
    /// any components of their configuration are outside of their position
    /// limits. This will NOT clear the LIMIT_VIOLATED flag from entries of
    /// mSolutions which are already tagged with it, even if they do not violate
    /// any limits.
    void checkSolutionJointLimits();

    /// Vector of solutions
    std::vector<Solution> mSolutions;

    /// Properties for this Analytical IK solver
    UniqueProperties mAnalyticalP;

  private:

    /// This maps the DOFs provided by getDofs() to their index in the Node's
    /// list of dependent DOFs. This map is constructed by constructDofMap().
    std::vector<int> mDofMap;

    /// List of extra DOFs in the module which are not covered by the Analytical
    /// IK implementation. The index of each DOF is its dependency index in the
    /// JacobianNode (i.e. the column it applies to in the Node's Jacobian).
    std::vector<size_t> mExtraDofs;

    /// A cache for the valid solutions. The valid and invalid solution caches
    /// are kept separate so that they can each be sorted by quality
    /// individually. Valid solutions will always be at the top of mFinalResults
    /// even if their quality is scored below the invalid solutions.
    std::vector<Solution> mValidSolutionsCache;

    /// A cache for the out of reach solutions.
    std::vector<Solution> mOutOfReachCache;

    /// A cache for solutions that violate joint limits
    std::vector<Solution> mLimitViolationCache;

    /// A cache for storing the current configuration
    Eigen::VectorXd mConfigCache;

    /// A cache for storing the current configuration so that it can be restored
    /// later. This is different from mConfigCache which will not be used to
    /// restore the configuration.
    Eigen::VectorXd mRestoreConfigCache;
  };

  /// If this IK module is set to active, then it will be utilized by any
  /// HierarchicalIK that has it in its list. If it is set to inactive, then it
  /// will be ignored by any HierarchicalIK holding onto it, but you can still
  /// use the solve() function with this.
  void setActive(bool _active=true);

  /// Equivalent to setActive(false)
  void setInactive();

  /// Returns true if this IK module is allowed to be active in a HierarchicalIK
  bool isActive() const;

  /// Set the hierarchy level of this module. Modules with a larger hierarchy
  /// value will be projected through the null spaces of all modules with a
  /// smaller hierarchy value. In other words, IK modules with a hierarchy level
  /// closer to 0 are given higher priority.
  void setHierarchyLevel(size_t _level);

  /// Get the hierarchy level of this modle.
  size_t getHierarchyLevel() const;

  /// When solving the IK for this module's Node, use the longest available
  /// dynamics::Chain that goes from this module's Node towards the root of the
  /// Skeleton. Using this will prevent any other branches in the Skeleton from
  /// being affected by this IK module.
  void useChain();

  /// Use all relevant joints on the Skeleton to solve the IK.
  void useWholeBody();

  /// Explicitly set which degrees of freedom should be used to solve the IK for
  /// this module.
  template <class DegreeOfFreedomT>
  void setDofs(const std::vector<DegreeOfFreedomT*>& _dofs);

  /// Explicitly set which degrees of freedom should be used to solve the IK for
  /// this module. The values in the vector should correspond to the Skeleton
  /// indices of each DOF.
  void setDofs(const std::vector<size_t>& _dofs);

  /// Get the indices of the DOFs that this IK module will use when solving.
  const std::vector<size_t>& getDofs() const;

  /// When a Jacobian is computed for a JacobianNode, it will include a column
  /// for every DegreeOfFreedom that the node depends on. Given the column index
  /// of one of those dependent coordinates, this map will return its location
  /// in the mDofs vector. A value of -1 means that it is not present in the
  /// mDofs vector and therefore should not be used when performing inverse
  /// kinematics.
  const std::vector<int>& getDofMap() const;

  /// Set an objective function that should be minimized while satisfying the
  /// inverse kinematics constraint. Pass in a nullptr to remove the objective
  /// and make it a constant-zero function.
  void setObjective(const std::shared_ptr<optimizer::Function>& _objective);

  /// Get the objective function for this IK module
  const std::shared_ptr<optimizer::Function>& getObjective();

  /// Get the objective function for this IK module
  std::shared_ptr<const optimizer::Function> getObjective() const;

  /// Set an objective function that should be minimized within the null space
  /// of the inverse kinematics constraint. The gradient of this function will
  /// always be projected through the null space of this IK module's Jacobian.
  /// Pass in a nullptr to remove the null space objective.
  ///
  /// Note: The objectives given to setObjective() and setNullSpaceObjective()
  /// will always be superimposed (added together) via the evalObjective()
  /// function.
  void setNullSpaceObjective(
      const std::shared_ptr<optimizer::Function>& _nsObjective);

  /// Get the null space objective for this IK module
  const std::shared_ptr<optimizer::Function>& getNullSpaceObjective();

  /// Get the null space objective for this IK module
  std::shared_ptr<const optimizer::Function> getNullSpaceObjective() const;

  /// Returns false if the null space objective does nothing
  bool hasNullSpaceObjective() const;

  /// Set the ErrorMethod for this IK module. You can pass in arguments for the
  /// constructor, but you should ignore the constructor's first argument. The
  /// first argument of the ErrorMethod's constructor must be a pointer to this
  /// IK module, which will be automatically passed by this function.
  template <class IKErrorMethod, typename... Args>
  IKErrorMethod& setErrorMethod(Args&&... args);

  /// Get the ErrorMethod for this IK module. Every IK module always has an
  /// ErrorMethod available, so this is passed by reference.
  ErrorMethod& getErrorMethod();

  /// Get the ErrorMethod for this IK module. Every IK module always has an
  /// ErrorMethod available, so this is passed by reference.
  const ErrorMethod& getErrorMethod() const;

  /// Set the GradientMethod for this IK module. You can pass in arguments for
  /// the constructor, but you should ignore the constructor's first argument.
  /// The first argument of the GradientMethod's constructor must be a pointer
  /// to this IK module, which will be automatically passed by this function.
  template <class IKGradientMethod, typename... Args>
  IKGradientMethod& setGradientMethod(Args&&... args);

  /// Get the GradientMethod for this IK module. Every IK module always has a
  /// GradientMethod available, so this is passed by reference.
  GradientMethod& getGradientMethod();

  /// Get the GradientMethod for this IK module. Every IK module always has a
  /// GradientMethod available, so this is passed by reference.
  const GradientMethod& getGradientMethod() const;

  /// Get the Analytical IK method for this module, if one is available.
  /// Analytical methods are not provided by default. If this IK module does not
  /// have an analytical method, then this will return a nullptr.
  Analytical* getAnalytical();

  /// Get the Analytical IK method for this module, if one is available.
  /// Analytical methods are not provided by default. If this IK module does not
  /// have an analytical method, then this will return a nullptr.
  const Analytical* getAnalytical() const;

  /// Get the Problem that is being maintained by this IK module.
  const std::shared_ptr<optimizer::Problem>& getProblem();

  /// Get the Problem that is being maintained by this IK module.
  std::shared_ptr<const optimizer::Problem> getProblem() const;

  /// Reset the Problem that is being maintained by this IK module. This will
  /// clear out all Functions from the Problem and then configure the Problem to
  /// use this IK module's Objective and Constraint functions.
  ///
  /// Setting _clearSeeds to true will clear out any seeds that have been loaded
  /// into the Problem.
  void resetProblem(bool _clearSeeds=false);

  /// Set the Solver that should be used by this IK module, and set it up with
  /// the Problem that is configured by this IK module
  void setSolver(const std::shared_ptr<optimizer::Solver>& _newSolver);

  /// Get the Solver that is being used by this IK module.
  const std::shared_ptr<optimizer::Solver>& getSolver();

  /// Get the Solver that is being used by this IK module.
  std::shared_ptr<const optimizer::Solver> getSolver() const;

  /// Inverse kinematics can be performed on any point within the body frame.
  /// The default point is the origin of the body frame. Use this function to
  /// change the point that will be used. _offset must represent the offset of
  /// the desired point from the body origin, expressed in coordinates of the
  /// body frame.
  void setOffset(const Eigen::Vector3d& _offset = Eigen::Vector3d::Zero());

  /// Get the offset from the origin of the body frame that will be used when
  /// performing inverse kinematics. The offset will be expressed in the
  /// coordinates of the body frame.
  const Eigen::Vector3d& getOffset() const;

  /// This returns false if the offset for the inverse kinematics is a zero
  /// vector. Otherwise, it returns true. Use setOffset() to set the offset and
  /// getOffset() to get the offset.
  bool hasOffset() const;

  /// Set the target for this IK module.
  ///
  /// Note that a target will automatically be created for the IK module upon
  /// instantiation, so you typically do not need to use this function. If you
  /// want to attach the target to an arbitrary (non-SimpleFrame) reference
  /// frame, you can do getTarget()->setParentFrame(arbitraryFrame)
  void setTarget(std::shared_ptr<SimpleFrame> _newTarget);

  /// Get the target that is being used by this IK module. You never have to
  /// check whether this is a nullptr, because it cannot ever be set to nullptr.
  std::shared_ptr<SimpleFrame> getTarget();

  /// Get the target that is being used by this IK module. You never have to
  /// check whether this is a nullptr, because it cannot ever be set to nullptr.
  std::shared_ptr<const SimpleFrame> getTarget() const;

  /// Get the JacobianNode that this IK module operates on.
  JacobianNode* getNode();

  /// Get the JacobianNode that this IK module operates on.
  const JacobianNode* getNode() const;

  /// This is the same as getNode(). It is used by the InverseKinematicsPtr to
  /// provide a common interface for the various IK smart pointer types.
  JacobianNode* getAffiliation();

  /// This is the same as getNode(). It is used by the InverseKinematicsPtr to
  /// provide a common interface for the various IK smart pointer types.
  const JacobianNode* getAffiliation() const;

  /// Compute the Jacobian for this IK module's node, using the Skeleton's
  /// current joint positions and the DOFs that have been assigned to the
  /// module.
  const math::Jacobian& computeJacobian() const;

  /// Get the current joint positions of the Skeleton. This will only include
  /// the DOFs that have been assigned to this IK module, and the components of
  /// the vector will correspond to the components of getDofs().
  Eigen::VectorXd getPositions() const;

  /// Set the current joint positions of the Skeleton. This must only include
  /// the DOFs that have been assigned to this IK module, and the components of
  /// the vector must correspond to the components of getDofs().
  void setPositions(const Eigen::VectorXd& _q);

  /// Clear the caches of this IK module. It should generally not be necessary
  /// to call this function. However, if you have some non-standard external
  /// dependency for your error and/or gradient method computations, then you
  /// will need to tie this function to something that tracks changes in that
  /// dependency.
  void clearCaches();

protected:

  /// The InverseKinematics::Objective Function is simply used to merge the
  /// objective and null space objective functions that are being held by an
  /// InverseKinematics module. This class is not meant to be extended or
  /// instantiated by a user. Call InverseKinematics::resetProblem() to set
  /// the objective of the module's Problem to an InverseKinematics::Objective.
  class Objective final : public Function, public optimizer::Function
  {
  public:

    /// Constructor
    Objective(InverseKinematics* _ik);

    /// Virtual destructor
    virtual ~Objective() = default;

    // Documentation inherited
    optimizer::FunctionPtr clone(InverseKinematics* _newIK) const override;

    // Documentation inherited
    double eval(const Eigen::VectorXd& _x) override;

    // Documentation inherited
    void evalGradient(const Eigen::VectorXd& _x,
                      Eigen::Map<Eigen::VectorXd> _grad) override;

  protected:

    /// Pointer to this Objective's IK module
    sub_ptr<InverseKinematics> mIK;

    /// Cache for the gradient of the Objective
    Eigen::VectorXd mGradCache;

    /// Cache for the null space SVD
    Eigen::JacobiSVD<math::Jacobian> mSVDCache;

    /// Cache for the null space
    Eigen::MatrixXd mNullSpaceCache;

  public:
    // To get byte-aligned Eigen vectors
    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
  };

  friend class Objective;

  /// The InverseKinematics::Constraint Function is simply meant to be used to
  /// merge the ErrorMethod and GradientMethod that are being held by an
  /// InverseKinematics module. This class is not meant to be extended or
  /// instantiated by a user. Call InverseKinematics::resetProblem() to set the
  /// first equality constraint of the module's Problem to an
  /// InverseKinematics::Constraint.
  class Constraint final : public Function, public optimizer::Function
  {
  public:

    /// Constructor
    Constraint(InverseKinematics* _ik);

    /// Virtual constructor
    virtual ~Constraint() = default;

    // Documentation inherited
    optimizer::FunctionPtr clone(InverseKinematics* _newIK) const override;

    // Documentation inherited
    double eval(const Eigen::VectorXd& _x) override;

    // Documentation inherited
    void evalGradient(const Eigen::VectorXd& _x,
                      Eigen::Map<Eigen::VectorXd> _grad) override;

  protected:

    /// Pointer to this Constraint's IK module
    sub_ptr<InverseKinematics> mIK;
  };

  friend class Constraint;

  /// Constructor that accepts a JacobianNode
  InverseKinematics(JacobianNode* _node);

  /// Gets called during construction
  void initialize();

  /// Reset the signal connection for this IK module's target
  void resetTargetConnection();

  /// Reset the signal connection for this IK module's Node
  void resetNodeConnection();

  /// Connection to the target update
  common::Connection mTargetConnection;

  /// Connection to the node update
  common::Connection mNodeConnection;

  /// True if this IK module should be active in its IK hierarcy
  bool mActive;

  /// Hierarchy level for this IK module
  size_t mHierarchyLevel;

  /// A list of the DegreeOfFreedom Skeleton indices that will be used by this
  /// IK module
  std::vector<size_t> mDofs;

  /// Map for the DOFs that are to be used by this IK module
  std::vector<int> mDofMap;

  /// Objective for the IK module
  std::shared_ptr<optimizer::Function> mObjective;

  /// Null space objective for the IK module
  std::shared_ptr<optimizer::Function> mNullSpaceObjective;

  /// The method that this IK module will use to compute errors
  std::unique_ptr<ErrorMethod> mErrorMethod;

  /// The method that this IK module will use to compute gradients
  std::unique_ptr<GradientMethod> mGradientMethod;

  /// If mGradientMethod is an Analytical extension, then this will have the
  /// same value is mGradientMethod. Otherwise, this will be a nullptr.
  ///
  /// Note that this pointer's memory does not need to be managed, because it is
  /// always either nullptr or a reference to mGradientMethod.
  Analytical* mAnalytical;

  /// The Problem that will be maintained by this IK module
  std::shared_ptr<optimizer::Problem> mProblem;

  /// The solver that this IK module will use for iterative methods
  std::shared_ptr<optimizer::Solver> mSolver;

  /// The offset that this IK module should use when computing IK
  Eigen::Vector3d mOffset;

  /// True if the offset is non-zero
  bool mHasOffset;

  /// Target that this IK module should use
  std::shared_ptr<SimpleFrame> mTarget;

  /// JacobianNode that this IK module is associated with
  sub_ptr<JacobianNode> mNode;

  /// Jacobian cache for the IK module
  mutable math::Jacobian mJacobian;
};

typedef InverseKinematics IK;

} // namespace dynamics
} // namespace kido

#include "kido/dynamics/detail/InverseKinematics.hpp"

#endif // KIDO_DYNAMICS_INVERSEKINEMATICS_HPP_