Abstract
Multimodal tactile sensing could potentially enable robots to improve their performance at manipulation tasks by rapidly discriminating between task-relevant objects. Data-driven approaches to this tactile perception problem show promise, but there is a dearth of suitable training data. In this two-page paper, we present a portable handheld device for the efficient acquisition of multimodal tactile sensing data from objects in their natural settings, such as homes. The multimodal tactile sensor on the device integrates a fabric-based force sensor, a contact microphone, an accelerometer, temperature sensors, and a heating element. We briefly introduce our approach, describe the device, and demonstrate feasibility through an evaluation with a small data set that we captured by making contact with 7 task-relevant objects in a bathroom of a person's home.
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