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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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Biologically Inspired Robotics

Demonstrated at Shikoku Research Center of Japan National Agricultural Research Center for Western Region.

Intelligence can only be determined by the dynamic interaction with the world. Recent studies in artificial intelligence and robotics suggest that even very simple biological creatures exhibit desirable functionality and boast far greater robustness than human-designed systems. This project focuses on using the biologically-inspired approaches to design an evolutionary autonomous mobile robot that is able to navigate in a poorly defined environment. The implementation of complex artificial intelligence systems can be approached by decomposing the global tasks into simpler, well-specified behaviors which are easier to design and can be tuned independently of each other. The behavior-based approach is chosen to build the control system of the robot. Robot behaviors can be implemented as a set of fuzzy rules which mimic expert knowledge in specific tasks. Behaviors usually emerge from implicit knowledge of the underlying process that can be converted into a set of linguistic variables and fuzzy rules. A vision-based landmark recognition system for robot navigation tasks is implemented as the highest layer. A novel search method, based on genetic algorithms for pattern recognition in digital images, is proposed and implemented in the developed mobile robot to generate desired behaviors.

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