Ruckig can be used flexibly for any underlying space with any number of degrees of freedom. For generating motions in Cartesian space, you need to find a representation that then can be used as input for Ruckig. There exist quite a few representations, from Euler angles to axis-angle to quaternion representations, each with different pros and cons.
As a rule of thumb, we recommend an axis-angle representation for Cartesian poses. In particular it allows to find a fixed axis between a start and a goal pose, and then the actual motion can be parametrized by three translation DoF and a single rotational DoF (the angle). This is very easy to implement, however only works if the start and goal velocities are zero.
Ruckig can be used flexibly for any underlying space with any number of degrees of freedom. For generating motions in Cartesian space, you need to find a representation that then can be used as input for Ruckig. There exist quite a few representations, from Euler angles to axis-angle to quaternion representations, each with different pros and cons.
As a rule of thumb, we recommend an axis-angle representation for Cartesian poses. In particular it allows to find a fixed axis between a start and a goal pose, and then the actual motion can be parametrized by three translation DoF and a single rotational DoF (the angle). This is very easy to implement, however only works if the start and goal velocities are zero.