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Graduate School of Science and Engineering
Information and Computer Science

Intelligent Mechatro-Informatics Laboratory


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Telephone : +81-774-65-6410

Office : KE-208
Database of Researchers
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Telephone : +81-774-65-6434

Office : KE-209
Database of Researchers

Research Contents

By making mechatronic systems, such as those represented by robots, more advanced through a fusion of ICT technology and intelligent technologies, we can implement smart mechatronic information systems with a high affinity for people and the environment. This research laboratory is researching the sensing, control, information processing, and the system integration which are the fundamental technologies to construct these kinds of systems. Our current research themes are shown below.
<1> Vehicle automation
Autonomous vehicles such as mobile robots and unmanned vehicles have up until now been developed in fields for labor-savings and dangerous work such as factories, ports, construction, agriculture, forestry, and industrial plants. Recently, autonomous vehicles have expanded into fields in close contact with our daily lives such as the Advanced Safety Vehicle in ITS (Intelligent Transportation System), office and home service robots, welfare, and crime prevention/security robots. We can also hope for broad applications in the future. We are researching the following topics in order to implement intelligent vehicle systems that are safe and easily cooperate with people and the environment.

Sensing systems:
Multi-sensor systems to recognize self-location, the situation of surrounding vehicles, and the condition of the environment
Control systems:
Autonomous navigation, Multi-robot cooperation, Shared control
Safety systems:
Dependable (fault diagnosis/fault-tolerant control) systems that operate safely even when the system fails partially
<2> Intelligent control
To achieve intelligent human-machine systems, control, measurement and modeling of systems are important. In view of this point, we are researching the following topics.

Neural network control systems:
Both the flexibility and the learning ability of neural networks would be effective to achieve controlling of a wide class of system, e.g. dynamic systems and nonlinear systems. It is therefore important to clarify a method for designing a control system based on the neural networks and to evaluate its performance.
Man-machine system:
To develop intelligent robotic systems that operate flexibly by recognizing user's intentions, studies on hands-free control systems using physiological signals are conducted.


  • Robotics
  • Mechatro-information system
  • Vehicle automation
  • Sensing
  • Sensor fusion
  • Control
  • Neural networks
  • Nonlinear system
  • Man-machine system