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Hi!
I'm registering a topic to get consultancy on how to get prediction of the next state using the library.
I've go that the next state is processed using ukf.step().
But if my purpose is to get next state estimation then How this can be calculated with provided methods?
Thanks for the answer!
The text was updated successfully, but these errors were encountered:
Could you plwease also advise on the following...
I'm using MS VS 2015 and I'm trying to compile an example cukf.cpp from the library.
On the followign line of code
using CovarianceMatrix = Matrix<covariance_size(), covariance_size()>;
I've got compilation error:
error C2976: Eigen::Matrix: to few arguments.
and the reference is on Eigen Matrix:
template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
class Matrix
: public PlainObjectBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
{
public:
/** \brief Base class typedef.
* \sa PlainObjectBase
*/
Hi!
I'm registering a topic to get consultancy on how to get prediction of the next state using the library.
I've go that the next state is processed using ukf.step().
But if my purpose is to get next state estimation then How this can be calculated with provided methods?
Thanks for the answer!
The text was updated successfully, but these errors were encountered: