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I hold the position of full Professor at DIIAG and
I am head of ALCOR Laboratory.
FGM

 

Cognitive robotics is the science studying computational  models of robot cognition and its embedding within robot technologies.

Cognitive robotics merges the science of mental processes such as attention, perception, learning, short and long term memorization, reasoning, problem solving, planning and decision making, together with the science of information processing, sensory feedback and control.

Cognitive robotics fosters the invention of new conceived intelligent machines, it does so by integrating a complex body of components into the design of robot outfitted technologies.

ALCOR LAB research focuses on the following aspects of Cognitive Robotics:

Attention: you can see an example of our Gaze Machine on the left. In the picture I wear the Gaze Machine mounted on a fire fighter helmet, to protect myself, as I was going to explore a tunnel where a big accident was simulated. The Gaze Machine is also available as a pair of glasses, see here for a description and some videos. Robot Attention is about what is interesting and why in a scene. What is interesting is salient. A robot targeting what is salient can exploit high resolution vision in the region of interest, so that all its processes and computational activities are not overloaded.

 

3D reconstruction of large scale outdoor environments: both our robots and the gaze machine are endowed with stereo pairs. Robot vision – likewise the wearable cameras such as the Gaze Machine – cannot be compared with hand held cameras. A hand held camera incorporates some implicit attention mechanism, as humans direct instinctively the camera towards interesting objects and the hand imparts to the camera a smooth motion which is far different from the robot mounted head or the human head-eyes system. 3D reconstruction of large scale outdoor environments requires both localization, and to transform point clouds into meshes to provide the robot with a good estimate of traversable terrains. 3D reconstruction is also needed to understand the environment. The advantage of visual reconstruction, as opposed to laser point cloud, is that vision can provide a very dense and high resolution reconstruction where it is needed, because it can be focused. The next step in cognitive robotics is to make robots able to navigate any kind of environment.

Human motion analysis: this is studied to make robot proactive.  We are now building a database of motions that can be used for our applications. Note that human motion is not necessarily the same thing as human action or human gesture.

Planning: robot planning is about a  full hierarchy of decision steps, from elementary control issues, like the velocity necessary to overcome an obstacle, up to managing tasks and a whole mission. Decision levels range from early stimuli to the formation of an appropriate model of the world. A model of the world cannot be defined a priori nor can be learned abruptly. Understanding the structure of a good knowledge of what the robot has to do in the world is a major issue and concerns high level planning, task switching, path planning and motion planning.

 

Augmented simulation environment: how to manage knowledge acquisition for several robot activities. One way of talking to your robot and explaining it what should be done under certain circumstances is to letting the robot experience some specific event and showing it the right response. This can be done by augmenting its reality, not yours.

Current Projects:
TRADR
NIFTi
SARFIRE

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