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Humanoid Sensing and Perception

Humanoid Sensing and Perception

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.

Laboratories

Laboratories

Our research tool is the iCub platform. We are one of the core groups of the iCub Initiative and we contribute to its development.
We have access to the equipment of the iCub Initiative which includes among the other things: three fully-fledged iCub robots and related computing equipment, a small machine shop, mechanical and electronic design facilities.

The team is composed of computer scientists and engineers with competences ranging from computer vision, signal processing, machine learning to software engineering.
We work in close collaboration with other departments in IIT (see below) and have formal and informal international collaborations.

Collaborations

Collaborations

Robotics is a strongly interdisciplinary field to achieve our goals we work in close interaction with other groups at IIT.

  • Giorgio Metta: iCub Facility
  • Lorenzo Rosasco: Laboratory for Computational and Statistical Learning
  • Alessio Del Bue: Visual Geometry and Modelling Lab
  • Nikos Tsagarakis: software for whole-body control
  • Lucia Beccai: human-like flexible tactile sensors

Projects

Projects

IIT People

IIT Publications List

Publications
2020
Bottarel F., Vezzani G., Pattacini U., Natale L.
GRASPA 1.0: GRASPA is a Robot Arm graSping Performance BenchmArk
IEEE Robotics and Automation Letters, vol. 5, (no. 2), pp. 836-843
2020
Maiettini E., Pasquale G., Rosasco L., Natale L.
On-line object detection: a robotics challenge
Autonomous Robots, vol. 44, (no. 5), pp. 739-757
2018
Vezzani G., Pattacini U., Pasquale G., Natale L.
Improving Superquadric Modeling and Grasping with Prior on Object Shapes
Proceedings - IEEE International Conference on Robotics and Automation, pp. 6875-6882
2018
Mar T., Tikhanoff V., Natale L.
What Can i Do with This Tool? Self-Supervised Learning of Tool Affordances from Their 3-D Geometry
IEEE Transactions on Cognitive and Developmental Systems, vol. 10, (no. 3), pp. 595-610
2017
Vezzani G., Pattacini U., Battistelli G., Chisci L., Natale L.
Memory Unscented Particle Filter for 6-DOF Tactile Localization
IEEE Transactions on Robotics, vol. 33, (no. 5), pp. 1139-1155