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Artificial Intelligence and Robotics

The research in this area is at the intersection between Artificial Intelligence and Robotics, and has its roots in the early AI research that targeted robots as embodiments of the intelligent agent.

The key scientific challenge, which has received a significant push by the recent developments in sensor technology and robotics, is the ability to deal with manifold representations of knowledge that enable robots to perform complex tasks in a dynamic, unknown environment populated by other (robotic and human) agents. One section of the work aims at analyzing perceptual data to create a rich world model, through the interpretation of sensor data and/or data coming from other information sources, including spoken language understanding and semantic representations of the environment. Another section of the research aims at developing various types of inference to support the actions of the robot in the environment, in particular within social contexts and in the interaction with the user. Both perception and action are often addressed in scenarios where multiple agents cooperate both in distributed perception and in task execution.

The research group leverages its extensive experience gained from participating in robotic competitions such as RoboCup, which began in 1998. These competitions span various domains, including robot soccer, where the lab actively engages with the SPQR Team in the Standard Platform League using humanoid robots, as well as competitions focused on Rescue, @Home, and @Work scenarios. Hence, one characterizing aspect of the research approach is a strong emphasis on the experimental validation of the proposed technical solutions through the implementation of system prototypes and their evaluation through suitable benchmarking methodologies.

The application domains, where the research ideas have been tested and experimentally evaluated, include virtual agents and multi-robot systems in soccer, emergency response robots, surveillance, precision agriculture and service robots. Specifically, the problem of sensor fusion and situation awareness has been targeted in the framework of maritime surveillance.

Several open-source hardware and software components and data sets are released and listed on our Web site www.diag.uniroma1.it/˜labrococo. They include the design of a small mobile robot MARRtino, the software libraries Petri Net Plans, SLAM pipelines (SRRG), soccer robot vision data set, IMBS, FHIS, PTracking, NICP, MODIM, Easy-DepthCalibration, the data sets for maritime surveillance (MarDT), the spoken language processing chain LU4R (in collaboration with Univ. Tor Vergata) and the data set for spoken command understanding (Huric).

The group has a solid tradition of cooperation with other research groups worldwide, and is very interested in establishing new collaborations and hosting foreign researchers and students.

 

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23Feb 24

Professor Manuela M. Veloso

24Nov 23

Janusz Kacprzyk, Gia Sirbiladze, Bezhan Ghvaberidze

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