We study distributed coverage of environments with unknown extension using a team of networked miniature robots analytically and experimentally. Algorithms are analyzed by incrementally raising the abstraction level starting from physical robots, to realistic and discrete event system (DES) simulation. The realistic simulation is calibrated using sensor and actuator noise characteristics of the real platform and serves for calibration of the DES microscopic model. The proposed algorithm is robust to positional noise and communication loss, and its performance gracefully degrades for communication and localization failures to a lower bound, which is given by the performance of a non-coordinated, randomized solution. Results are validated by real robot experiments with miniature robots of a size smaller than 2 cm×2 cm×3 cm in a boundary coverage case study. Trade-offs between the abilities of the individual platform, required communication, and algorithmic performance are discussed.