Dipartimento d'Ingegneria

Automatics - Automatica

Control and Automation – Controlli ed Automazione
Activity in Control and Automation at DIEI can be divided into the following research areas

Aerial and Underwater Robotics: Over the years many lines of research have been activated in the area of Aerial Robotics. This include design, deployment and testing of UAVs systems, flight guidance and control schemes, sensors and actuator faults diagnosis schemes, fault tolerant control, non-linear adaptive and learning control, optical feedback based control schemes for UAVs in flight operations such as autonomous aerial refuelling. Vision based localization and navigation problems are studied also in the Area of Autonomous Underwater Vehicles (AUV).

Perception in Robotics: Perception is one of the key enablers to deploy autonomous robots in realistic and unpredictable environments. Research in this area focuses on the development of robot perception systems, with specific interest for systems employing vision and range sensors. Current activities cover the study of innovative methodologies for sensor fusion, the use of computer vision and machine learning tools for scene modelling, place recognition, loop closing and in general localization problems.

Medical and biological applications: Development of engineering tools for medical and biological applications, such as artificial pancreas simulation, hydrocephalus pressure control and management, systems biology.

Technology transfer: The group is also involved in a number of industrial technology transfer projects covering the above areas, as well as general control, and automation problems. In this context the research mission of the group is to develop solutions and methods of interest for service and industrial robotics, autonomous systems, with application to mobile robots, underwater vehicles, and unmanned aerial vehicles.

This project is aimed at the integration among the individual, collective and communication controls of a multi robot system to ensure full operation capabilities. The chosen test case will be based on an underwater swarm of simple autonomous mobile communication nodes with sensing capabilities for environmental monitoring. The global control architecture will come from the study of an equilibrium among three basic issues: the human furnished goals, the need for reliable inter-nodal communications (that affects the geometrical configuration), the local planning and the priorities of the single individual. The equilibrium will change depending on the assigned tasks, the survival risk associated to the operation of each robot and the risk associated to the loss of connection with the multi body system as a whole. In order to minimize the computational effort of the single individual a neural network approach will be studied for the management of the supervising equilibrium.

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