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RESEARCH PROGRAM

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Keywords
COOPERATIVE CONTROL; AUTONOMOUS VEHICLES; MISSION PLANNING

Control Management of Cooperative Heterogeneous Unmanned Vehicles: Analytical Methods and Experimental Validation

Università di Pisa
Abstract
The objective of the proposed research is to develop a methodology for the management and control of heterogeneous vehicles (land
and air for instance), so that they are capable of operating autonomously and in a cooperative fashion. In addition, the methodology
will be tested experimentally by selecting a scenario consisting of up to three vehicles (two air vehicles or UAVs, and one ground
vehicle or GAV). The problem of managing the mission of several autonomous vehicles, possibly of different nature, such as land,
air, and sea vehicles, has become of enormous interest from the standpoint of basic as well as applied research, for a variety of
potential applications, included its potential contribution to defense and prevention against terrorist attacks. In this field, platform
technology has dramatically improved in recent years (material properties, miniaturization of components, energy storage, computer
speed and storage capacity,..), however reliable and flexible high level automation and "intelligence" are still open questions. The
aim of the project is to contribute to the latter aspects in terms of trajectory planning optimization in the presence of static (known)
and partially unknown obstacles, to the definition of appropriate sensor suite and sensor fusion, and to the evaluation of
communication links and their fault tolerance requirements. In order to test the developed methodologies, an >>>

Principal Investigator
Mario INNOCENTI Università di PISA
Research Objectives
The aim of the proposed research program is the development and experimental validation of a trajectory planning, management and control for a heterogeneous system of autonomous, cooperative vehicles. The proposed approach deals with analytical and application related aspects of levels of automation, information acquisition and data exchange (that is "intelligence"), so that each vehicle can participate to the whole mission or part of it optimizing its contribution to the betterment of the entire system.
In recent years, the general area of autonomous vehicles has received a considerable attention from the standpoint of basic research, applied research, and prototypical and production implementation. Development of "classical automation", that is control system, guidance, navigation, and path planning has greatly benefited by improved quality of sensors and actuators, their size reduction, by the increasing computation speed, and by reliable wireless communication and localization tools (GPS); thus allowing the use of more complex dynamic and kinematic control system methods. It has been possible to design autonomous systems ranging from mobile robots in a limited structured environment, to underwater vehicles for unmanned scientific exploration; from unmanned aerial vehicles for reconnaissance, search and rescue, to ground vehicles for de-mining and planetary exploration. Brilliant as the results are to the scientific world, as well as to the general public >>>

Timescale
24 months
National and international background
The research project has the aim of designing a management system for path planning, navigation and guidance of autonomous, cooperative heterogeneous vehicles. There are many foreseen uses for such systems that cover scientific applications, human and social aspects, defense and civilian protection inclusive of military and police tasks. In the sphere of interest of the present project we could mention as potential applications:
• Research and rescue operations in areas of morphologic asperities
• Reconnaissance and terrain mapping
• Surveillance operations in traffic congested areas and crowded areas
• Localization and relief operations after natural disasters such as earthquakes
• Cooperation to police and other authorities for border defense, terrorist attacks, handling and identification of hazardous material and mines.

In all these cases, the capability of using multiple autonomous cooperative vehicles in a closed loop fashion greatly increases the probability of success.
The proposed approach deals with analytical and experimental aspects for the integration of levels of automation, intelligent behavior, data exchange, so that each agent's dynamic properties are used optimally. The research team scientific capabilities are well integrated and complementary see [1], [2], [3], [4], [5], [6], they are documented in detail in the proposal written by each research unit, and some of the scientific personnel has >>>