Multimodal sensing is a research field and methodological approach focused on the synergistic acquisition, processing, and integration of data from two or more distinct sensing modalities. Its core objective is to overcome the inherent limitations of single-modality sensing by leveraging the complementary information provided by diverse sensor types (e.g., visual, tactile, thermal) to achieve a more comprehensive, robust, or nuanced perception and understanding of an environment, object, or phenomenon. This approach investigates methods for combining heterogeneous data streams, often employing fusion techniques, to enable enhanced capabilities such as improved accuracy, richer semantic insights, or more effective decision-making in complex systems.