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Research Interest
UAV for Forest Fire Management
Multi-Rotor Rotorcraft
Intelligent Transportation Systems
Multi-Agent Systems
Object Oriented Programming
Virtual Reality Modelling
Autonomous Mobile Robot
Industrial Overhead Cranes
Parking System Using FPGA
Artificial Neural Networks
Perception Models for Robots
Multiple UAVs and UGVs
Document Classification
Nuclear Inspection
Domestic Water Heater
Autonomous Underwater Vehicle
Motion Planning
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Coordinated Control of Multi-Agent Systems

Multi-agent systems represent a group of agents that work cooperatively to solve common tasks in a dynamic environment. The control of multi-agent systems relates to synthesizing control schemes for systems that are inherently distributed and composed of multiple interacting entities. Because of the wide applications of multi-agent theories in large and complex control systems, it is necessary to develop a framework to simplify the process of developing control schemes for multi-agent systems. A lot of architectures have been proposed for the control of multi-agent systems. While efficient in many aspects, these approaches are always problem dependent. In our research, a framework is proposed for the distributed control and coordination of multi-agent systems. In the proposed framework, the control of multi-agent systems is regarded as decentralized control and coordination of agents. Both the discrete dynamics and continuous dynamics are considered in this framework. The Lyapunov method is adopted to analyze the stability of multi-agent systems. The framework is applied to a heterogeneous multi-agent system that consists of an overhead crane, a mobile robot and a robot manipulator. Results show that the framework can model complex multi-agent systems.

Please download the mobile robot demo video here.

Please download the robot manipulator demo video here.

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