Communicating Physical Properties Through Robot Object Manipulation

Abstract

When verbal communication is limited, robots passing objects to humans without providing additional information (e.g., temperature, weight) can result in potential poor handovers and disappointing user experiences. To address this issue, we introduced a method for conveying object properties through robot manipulation. We began by proposing four criteria for selecting properties from two widely recognized sets: one focusing on the semantic features of objects and the other on tactile sensations. These properties were clustered into eight physical categories: hot, cold, heavy, light, slippery, sticky, fragile, and smelly. Professional actors were then recruited to demonstrate these properties through object manipulation, from which we extracted a set of fundamental yet expressive manipulation behaviors, i.e., key elements, that help people recognize these properties. These elements were implemented on a dual-arm robot, followed by an evaluation of their utility through participant feedback. To generate time-constrained sequences of elements, we developed a property-based motion planner that balances time and utility in conveying object properties. Results from a within-subjects study involving 20 participants showed that individuals could accurately interpret the properties conveyed by robot object manipulation, validating the effectiveness of the proposed approach.