ethz-asl/aslam_splines

B-spline implementations usable as design variables and expression sources for aslam_optimizer

aslam_splines's Issues

What is the starting point to learn templates?

Hi Hannes,

Thank you for the amazing work.
The templates are very involved to me. I look to learn about them.
Can you please provide a book or a link to start the learning?

Regards,

what is coefficients_ in follow link ?

aslam_splines/bsplines/include/bsplines/BSpline.hpp

Line 686 in d2c8c69

Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor> coefficients_;

got errors during "catkin build hand_eye_calibration_batch_estimation"

Got many errors for same reason "marked ‘override’, but does not override", here is one example:

/home/catkin_ws/src/aslam_splines/aslam_splines/include/aslam/splines/BSplineExpressions.hpp:67:37: error: ‘virtual Eigen::Vector3d aslam
::splines::BSplinePositionExpressionNode::evaluateImplementation() const’ marked ‘override’, but does not override
virtual Eigen::Vector3d evaluateImplementation() const override;

Another error which happened lot of times is "error: invalid new-expression of abstract class type", one example:

/home/catkin_ws/src/aslam_splines/aslam_splines/src/BSplineRSPoseDesignVariable.cpp: In member function ‘aslam::backend::TransformationExpression aslam::splines::BSplineRSPoseDesignVariable::transformation(double, double)’:
/home/catkin_ws/src/aslam_splines/aslam_splines/src/BSplineRSPoseDesignVariable.cpp:67:157: error: invalid new-expression of abstract class type ‘aslam::splines::RSLineDelayTransformationExpressionNode’
boost::shared_ptr root( new RSLineDelayTransformationExpressionNode( _bsplinePoseDV, _lineDelayDV, t0, line) );

Using gcc version of 5.5.0
Thks a lot for help!

The mathematical detail in BSpline::curveQuadraticIntegralDiag()

It's the same issue from ethz-asl/kalibr#383

Hello, everyone. I'm studying the code of kalibr and trying to figure out the algorithm details for IMU-Camera calibration. kalibr uses the BSpline to represent the trajectory of IMU(or camera), and in the BSpline initialization, the below methods are called.

1. void BSplinePose::initPoseSplineSparse(const Eigen::VectorXd & times, const Eigen::Matrix<double,6,Eigen::Dynamic> & poses, int numSegments, double lambda), see code in line
2. Then call void BSpline::initSplineSparse(const Eigen::VectorXd & times, const Eigen::MatrixXd & interpolationPoints, int numSegments, double lambda), see code in line

I'm trying to understand the mathematics detail in BSpline::initSplineSparse(). Currently, I have understand several things,

1. The method void BSpline::initSplineSparse() is the sparse version of `void BSpline::initSpline3()', see code in line
2. The initialization method will build a equation Ax = B
3. The first part of the equation is C(t) = U(t) * M * V, which means the BSpline value evaluated at time t will be C(t).
4. The second part of the equation assumes the quadratic integral is zero during each segment.

    // make this conditional on the order of the spline:
    if (splineOrder_ == 2)
        A += curveQuadraticIntegralDiag(W, 1);
    else
        A += curveQuadraticIntegralDiag(W, 2);

However, I couldn't understand the mathematical details in method Eigen::MatrixXd BSpline::curveQuadraticIntegralDiag(const Eigen::VectorXd& Wdiag, int derivativeOrder)(see code in line). Is anyone know the details? or some paper could be referenced?