Perception and characterization of materials using signal processing techniques

In this paper, we develop a methodology and a conceptual framework in which manipulations are undertaken for perceiving and characterizing materials. Within this framework, we distinguish different materials (unknown environments) by actively contacting and testing them, and by analyzing the resulting sounds using a microphone. For this implementation, we identify sensor-derived measures that are diagnostic of a material's properties, and use these measures to categorize the objects (or unknown environments) in their different material class. The parameter of characterization is the internal angle of friction of the materials. This parameter is determined by the relation of strain and stress properties. Using this theoretical approach and the experimental results, we conclude that the statement of shape-invariance of materials is critical and invalid in real cases.