About Laboratory

Systems that have the attributes (learning, intuition, creativity, adaptation, reasoning, etc..), Similar to biological organisms, called intelligent systems. Any system that can accept sensor information and has the ability to prosecute the efficiency and effective computer software, combined with one or more intelligent algorithms (an algorithm which can be biologically inspired, mathematically modeled, etc.). To perform functions such ascontrol, resource management, diagnostics, in order to achieve a given goal, called the intelligent system.
The basis of the intelligent system are: sensor technology, technology, calculating, clever algorithms and communication technology.
The importance of intelligent systems is proportional to the increase in the use and implementation of sensor technology.Examples of intelligent systems found everywhere, ranging from the home application (washing machines), robotic systems (robots in the form of insects, robots that walk), transport systems (systems for automatic traffic management), diagnostic system (Intelligent on-line machine diagnostics errors), and the like. (Read less)

The Intelligent Systems Laboratory (ICBL) , Faculty of Mechanical Engineering  is designed to facilitate the development of cross-disciplinary courses and provide exciting collaborative research possibilities. The ISL enables both students and faculty to investigate, design, and implement control algorithms using non-traditional techniques derived from various subdisciplines of Artificial Intelligence, such as fuzzy logic, neural networks, genetic algorithms, hybrid approaches, etc. The ICBL also furnishes opportunities to work with people from other disciplines. Such collaborative work gives students the experience of working with non-majors on a joint project, an experience they will all need to be successful in their careers. The robotics equipment acquired for the ICBL is to be used to support instruction of both undergraduate and graduate students through new and recently modified courses in the areas of Machine Intelligence, Intelligent Systems Design and Applications, Intelligent Control, Autonomous Robots, and others. Robotic kits at the basic, intermediate, and advanced levels are used to facilitate research, research training, and integrated research/education activities at various academic levels.

The ICBL was partially funded in 2008 through 2009 by Ministry of Science and Tehnology  trough projects Fuzzy Systems and Robi001.

The Intelligent Systems Laboratory (ICBL) , Faculty of Mechanical Engineering  is designed to facilitate the development of cross-disciplinary courses and provide exciting collaborative research possibilities. The ISL enables both students and faculty to investigate, design, and implement control algorithms using non-traditional techniques derived from various subdisciplines of Artificial Intelligence, such as fuzzy logic, neural networks, genetic algorithms, hybrid approaches, etc. The ICBL also furnishes opportunities to work with people from other disciplines. Such collaborative work gives students the experience of working with non-majors on a joint project, an experience they will all need to be successful in their careers. The robotics equipment acquired for the ICBL is to be used to support instruction of both undergraduate and graduate students through new and recently modified courses in the areas of Machine Intelligence, Intelligent Systems Design and Applications, Intelligent Control, Autonomous Robots, and others. Robotic kits at the basic, intermediate, and advanced levels are used to facilitate research, research training, and integrated research/education activities at various academic levels.
The ICBL was partially funded in 2008 through 2009 by Ministry of Science and Tehnology  trough projects Fuzzy Systems and Robi001.

The Intelligent Systems Laboratory (ICBL) , Faculty of Mechanical Engineering  is designed to facilitate the development of cross-disciplinary courses and provide exciting collaborative research possibilities. The ISL enables both students and faculty to investigate, design, and implement control algorithms using non-traditional techniques derived from various subdisciplines of Artificial Intelligence, such as fuzzy logic, neural networks, genetic algorithms, hybrid approaches, etc. The ICBL also furnishes opportunities to work with people from other disciplines. Such collaborative work gives students the experience of working with non-majors on a joint project, an experience they will all need to be successful in their careers. The robotics equipment acquired for the ICBL is to be used to support instruction of both undergraduate and graduate students through new and recently modified courses in the areas of Machine Intelligence, Intelligent Systems Design and Applications, Intelligent Control, Autonomous Robots, and others. Robotic kits at the basic, intermediate, and advanced levels are used to facilitate research, research training, and integrated research/education activities at various academic levels.The ICBL was partially funded in 2008 through 2009 by Ministry of Science and Tehnology  trough projects Fuzzy Systems and Robi001.

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