This chapter surveys the practices that are being employed in experimentally assessing the special class of computational models embedded in robots. The assessment of these models is particularly challenging mainly due to the difficulty of accurately estimating and modeling the interactions between the robots and their environments, especially in the case of autonomous robots, which make decisions without continuous human supervision. The field of autonomous robotics has recognized this difficulty and launched a number of initiatives to deal with it. This chapter, after a conceptual premise and a broad introduction to the experimental issues of robotics, critically reviews these initiatives that range from taking inspiration from traditional experimental practices, to simulations, benchmarking, standards, and competitions.