AU Dataset for Visuo-Haptic Object Recognition for Robots
This provides a resource for researchers in robotics and AI working on multimodal object recognition, though it is incremental as it adds to existing datasets.
The authors tackled the scarcity of multimodal datasets for object recognition by creating a new dataset containing visual, kinesthetic, and tactile data for 63 objects with some ambiguity, aiming to support research in sensory integration.
Multimodal object recognition is still an emerging field. Thus, publicly available datasets are still rare and of small size. This dataset was developed to help fill this void and presents multimodal data for 63 objects with some visual and haptic ambiguity. The dataset contains visual, kinesthetic and tactile (audio/vibrations) data. To completely solve sensory ambiguity, sensory integration/fusion would be required. This report describes the creation and structure of the dataset. The first section explains the underlying approach used to capture the visual and haptic properties of the objects. The second section describes the technical aspects (experimental setup) needed for the collection of the data. The third section introduces the objects, while the final section describes the structure and content of the dataset.