I have been using the acados Python interface to prototype a trajectory optimization approach for my project. It has been extremely productive to use CasADi for rapidly making changes to the NLP formulation for which I can quickly generate and run a solver
to verify convergence. I then link the solver with a C++ executable for my application.
I am wondering if using symbolic expressions for everything has a “price”.
Let’s say we have some polytopic constraints that could be expressed in matrix form, but we use symbolic expressions for convenience. Will we be missing out on anything?
I read that using cost module
auto converts cost functions that can be expressed as least squares to matrix form, so I assume there is an advantage to this. I suppose that it would come from skipping the linearization step. Does acados do this behind the scenes for constraints as well?
Thanks in advance