Control systems benchmarking is critical in bridging the gap between theory and practice in robotics. This chapter proposes two benchmarks for an autonomous holonomic robot. The first benchmark uses a digital twin to model the perception of the robot and localization, enabling the testing of control algorithms in a controlled environment. The second one employs a scaled low-cost prototype to test more challenging elements of the robotics pipeline that are difficult to model, such as communication and connectivity, environmental disturbances, design shortcomings, and real-world unpredictability. The results demonstrate how digital twins and low-cost prototypes offer a cost-effective way of assessing control algorithm performance before implementing expensive robotic systems.