Is there any reason why providing symbolic features into an MLP wouldn't outperform feeding raw pixels to a CNN in a RL task?
If the features are able to fully define the image, there would be no reason to use a pixel-based approach.  You are essentially performing lossless compression and (nearly) instantly acquiring a feature set, so you would see a dramatic performance difference between the CNN and MLP.

If you needed a quick solution, CNNs are great out-of-the-box algorithms, but if you are willing to put in the time to develop an MLP, it would provide a performance boost without losing accuracy.