In this paper, a novel automated data acquisition methodology is presented for chipless RFID systems. The proposed method utilises a Raspberry Pi to act as an interface between a vector network analyser and a universal arm robot to perform automated measurements. A 98% improvement in data acquisition time is achieved when compared to standard manual data collection methodology. The system is validated by collecting 9,600 radar cross section electromagnetic signatures from a 3-bit chipless RFID capacitive sensor tag for five different cases at four positions. By enabling large, efficient, and accurate data collection, this methodology can support the development of machine learning models that can improve the performance and functionality of chipless RFID technology.