The proposed semi-supervised novelty detection approach demonstrated in the EPSNoDe framework can be extended to other types of localization technologies beyond UWB to provide a more general solution for reliable robot localization in evolving environments. By adapting the framework to work with different sensor modalities and data sources, such as LiDAR, RFID, or magnetic field sensors, the methodology can be applied to a wide range of localization systems.
For example, LiDAR sensors can provide detailed 3D maps of the environment, which can be used in conjunction with the EPSNoDe framework to detect anomalies and changes in the surroundings. Similarly, RFID tags can offer unique identifiers for different locations, enabling the framework to detect deviations from the expected RFID patterns. Magnetic field sensors can provide information about the magnetic field variations caused by obstacles or metallic objects, further enhancing the framework's ability to detect novelties in the environment.
By adapting the semi-supervised novelty detection approach to different localization technologies, the framework can offer a versatile and adaptable solution for robot localization in diverse and dynamic environments. This extension can lead to more robust and reliable localization systems that can effectively navigate and operate in complex real-world scenarios.