Best practices for functions with multiple Eigen objects as parameters

Best practices for functions with multiple Eigen objects as parameters

I find the design of functions with Eigen objects as parameters
cumbersome. While the information in the Eigen Documentation is helpful,
it suggests an awkward approach for the template arguments. Suppose, we
want to write a geometric routine like a line-plane-intersection. A simple
and transparent approach would be:
template<typename _Tp>
bool planeLineIntersect(const Eigen::Matrix<_Tp, 3, 1>& planePoint,
const Eigen::Matrix<_Tp, 3, 1>& planeNormal,
const Eigen::Matrix<_Tp, 3, 1>& linePoint,
const Eigen::Matrix<_Tp, 3, 1>& lineDir,
Eigen::Matrix<_Tp, 3, 1>& intersectionPoint)
This looks relatively pleasing and someone that looks at this can learn
that every parameter shall be a 3D vector of the same type. However, this
does not allow for Eigen expressions of any kind (we would have to call
Eigen::Matrix constructors for every expression, that we use). If
expressions are used with this, we need to create unnecessary temporaries.
The suggested solution is:
template<typename Derived1, typename Derived2, typename Derived3, typename
Derived4, typename Derived5>
bool planeLineIntersect(const Eigen::MatrixBase<Derived1>& planePoint,
const Eigen::MatrixBase<Derived2>& planeNormal,
const Eigen::MatrixBase<Derived3>& linePoint,
const Eigen::MatrixBase<Derived4>& lineDir,
const Eigen::MatrixBase<Derived5>& intersectionPoint)
This does not reveal anything about the matrices that are expected, nor
which parameters are used for input and output, as we have to const-cast
the intersectionPoint to allow for expressions in output parameters. As I
understand it, this is the only way to allow for Eigen expressions in all
function parameters. Despite the unelegant expression support, the first
snippet still seems more likable to me.
My Questions:
Would you consider the second code snippet the best solution for this
example?
Do you ever use the const-cast solution for output parameters or do you
think it is not worth the loss in transparency?
What guidelines/best practices do you use for Eigen function writing?