Material Recognition via Heat Transfer Given Ambiguous Initial Conditions
This research addresses the challenge of robust material recognition for robots using thermal sensing, particularly under ambiguous initial conditions, which is crucial for robotic manipulation and interaction.
This paper investigates the ambiguity in material recognition via heat transfer when initial conditions are varied, showing that both humans and robots confuse materials under such circumstances. The study demonstrates that robots can overcome this ambiguity with 100% accuracy using two temperature sensors at different initial temperatures, significantly outperforming human accuracy of 5%.
Humans and robots can recognize materials with distinct thermal effusivities by making physical contact and observing temperatures during heat transfer. This works well with room temperature materials and humans and robots at human body temperatures. Past research has shown that cooling or heating a material can result in temperatures that are similar to contact with another material. To thoroughly investigate this perceptual ambiguity, we designed a psychophysical experiment in which a participant discriminates between two materials given ambiguous initial conditions. We conducted a study with 32 human participants and a robot. Humans and the robot confused the materials. We also found that robots can overcome this ambiguity using two temperature sensors with different temperatures prior to contact. We support this conclusion based on a mathematical proof using a heat transfer model and empirical results in which a robot achieved 100% accuracy compared to 5% human accuracy. Our results also indicate that robots can use subtle cues to distinguish thermally ambiguous materials with a single temperature sensor. Overall, our work provides insights into challenging conditions for material recognition via heat transfer, and suggests methods by which robots can overcome these challenges to outperform humans.