- 1. Control systems design
- Advanced mechatronics control (Figs. 1, 2, 3)
We investigate control theory for periodic motions (such as repetitive and
delayed feedback control) and its application to power-assisted control for
electric bicycles and analysis of passive dynamic walking.
- Vehicle control using robust control theory (Fig. 3)
We conduct theoretical and experimental studies on motion control for
- 2. Sensing & signal processing
- Visual feedback and sensor networks
By regarding sensing technology as a component of a control system, we
work on visual feedback control and sensor networks for mobile robots.
- Learning/Adaptive theory applied to various systems (Fig. 5)
We study intelligent signal processing such as independent component
analysis and feedback error learning. We also study their applications to
system identification for control.
- 3. Machine learning for robotics
- Motor skill learning for humanoid robots (Fig. 4)
We are developing novel methods that enable robots to learn complex
motor skills (e.g., biped walking, T-shirt wearing and clothing assistance)
by optimal control and reinforcement learning.
- Constructing practical myoelectric interfaces for robot control (Fig. 5)
We construct a myoelectric interfaces robust to postural changes, sweating,
and muscular fatigue, using a surface electromyograms (sEMG) via
modern machine learning methods.
We welcome motivated students from various fields including mechanical/electrical engineering, mathematical/physical science, as well as computer
science. The faculty staff guides students individually, taking into account
their backgrounds, and assists them in mastering mathematical system
approaches by the end of their course. Thereby they acquire a wide range of
technical skills from fundamental theories to applications. The students in our
lab are highly-motivated hard-workers, cooperative and eager to learn from
others. We anxiously await such students, both from Japan and from abroad.
Fig.1 Entertainer robot "SOMENOSUKE"
Fig.2 Power assist control for
Fig.3 McKibben pneumatic artificial
muscle system and collision
avoidance of vehicles
Fig.4 Dual arm/hand robot and
Fig.5 Acquired table-tennis skills and