The iCub multisensor datasets for robot and computer vision applications

Multimodal information can significantly increase the perceptual capabilities of robotic agents, at the cost of a more complex sensory processing. This complexity can be reduced by employing machine learning techniques, provided that there is enough meaningful data to train on. This paper reports on creating novel datasets constructed by employing the iCub robot equipped with an additional depth sensor and color camera. We used the robot to acquire color and depth information for 210 objects in different acquisition scenarios. At the end, the results were large scale datasets that can be used for robot and computer vision applications: multisensory object representation, action recognition, rotation and distance invariant object recognition.