A multimodal tactile dataset for dynamic texture classification.

ABSTRACT: Reproducing human-like dexterous manipulation in robots requires identifying objects and textures. In unstructured settings, robots equipped with tactile sensors may detect textures by using touch-related characteristics. An extensive dataset of the physical interaction between a tactile-enable robotic probe is required to investigate and develop methods for categorizing textures. Therefore, this motivates us to compose a dataset from the signals of a bioinspired multimodal tactile sensing module while a robotic probe brings the module to dynamically contact 12 tactile textures under three exploratory velocities. This dataset contains pressure, acceleration, angular rate, and magnetic field variation signals from sensors embedded in the compliant structure of the sensing module. The pressu

SUBMITTER: Monteiro Rocha Lima B 

PROVIDER: S-EPMC10519821 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature