Today robots are largely used in factories but lack capabilities to sense and perceive the environment. They can interact with the environment only using accurate models and are not allowed to interact with humans. Programming robots is therefore expensive and time-consuming, and their use limited to very specific applications. The goal of our research is to develop humanoid robots that are progressively more autonomous and can effectively work in unstructured environments, operating in close interaction and cooperation with humans.
At this aim the Humanoid Sensing and Perception group studies algorithms and technologies that allow robots to sense the environment and react appropriately. Our strategy is to exploit the capability of robots to learn under human guidance or from the interaction with the environment by exploiting multiple sources of information (e.g. proprioception, vision, touch, and audition). Our activities focus on computer vision, tactile sensing and the development of the software technologies for seamless interaction of perception and action.
Humanoid Sensing and Perception
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Ceola F., Maiettini E., Pasquale G., Meanti G., Rosasco L., Natale L.
Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot
IEEE Transactions on Robotics, vol. 38, (no. 5), pp. 3154-3172