I have been accepted by a professor for an undergraduate research opportunity in the area of surgical robotics, where I will be working with a Ph.D. student in control and applying some machine learning to make control easier.

A bit about my self - I have done college courses on classical and modern control theory and have a good understanding of nonlinear, adaptive and optimal control along with classical techniques like Bode, Nyquist plot. I have also worked on a couple of projects like quadrotor control using lqr, full state feedback, $H_{\infty}$ and SMC. I have also worked on controlling a robotic arm. I haven't really worked on hardware though; everything has been simulations in Matlab or Python.

What else should I do or concepts that I should learn before I start the research intern, so I won't lag behind on any concepts or skills and won't be a bother to the Ph.D./professor?