I always see the Kalman filter used with such input data. For example, the inputs are commonly a position and the correspondent velocity:
$$ (x, \dfrac{dx}{dt}) $$
In my case, I only have 2D positions and angles at each sample time:
$$ P_i(x_i, y_i) \qquad \text{and} \qquad (\alpha_1, \alpha_2, \alpha_3) $$
Should I compute velocities for each point and for each angle to be able to fit the Kalman framework?