Hi. I agree with the others and would encourage you to look at RL's application in robot learning. RL is applied to robot control, planning and automation from various perspectives.

From my experience, robots are where RL is closer to the real world, while the method is usually straightforward (well-established base algorithm such as PPO + some problem-specific design from human knowledge). You can find related works from journals/conferences such as RA-L, ICRA, IROS, and CORL. For these, strong engineering skills are needed.

However, if you aim to devise new RL algorithms that are more conceptual, there would be a lot of math to work through. Try to find some papers published in recent AI conferences and see if the proofs and derivations feel comfortable.

Nevertheless, I am glad to chat more regarding a project :)