Research Topics

Now that ubiquitous society has come, computerized/intelligent control systems are achievable everywhere. Our laboratory is working on system control, machine learning, signal processing, and interdisciplinary study based on these topics. In what follows, after stating general overview, we show our current research topics. Please note that these are just examples and we always challenge a new topic.

— Intelligent System Control: What is our target —

As the term “control” is used in our daily life, this concept is familiar and basic. Control technology is widely used in industry, but at this moment only simple control laws are adopted in practice and higher performance is strongly desired. This can be achieved by modeling dynamics of the object and analyzing/designing the system in an intelligent way. It is also desirable to build a learning mechanism as a human shows improvement with his/her progress. It is thus our target to construct a highly intelligent control system. Because of its high level of abstraction, you might feel that it is not practical right now, but the knowledge you learn here will be surely useful when you enter the real world.

Robust Control / Adaptive control

We study advanced theories in post-modern robust/adaptive control and their applications. Various schemes of feedforward learning control(feedback error learning) are currently under investigation.

フィードバック誤差学習

Independent Component Analysis

In this research, we study system identification, fault detection, and disturbance rejection via independent component analysis.

独立成分分析

Probabilistic inference based optimal control / Reinforcement learning

We study stochastic optimal control and reinforcement learning.

確率推論

Motor Skill Learning for Humanoid Robots

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.

運動スキル学習

Full-body Exoskeleton Robot Control for Walking Assistance

We propose an adaptive walking assistance strategy to control a full-body exoskeleton robot using an oscillator model.
(joint work with ATR CNS)

歩行アシスト

Active Motion Planning of Robots Based on Information Theoretic Criteria

We propose an active motion planning principle and its calculation algorithm based on information theoretic criteria such as the mutual information.

行動計画

Intrinsically Motivation for Autonomous Robots

In order for the robot to truly autonomously work, it is necessary for the robot to determine the purpose by themselves rather than getting the purpose from designers. We are studying autonomous behavior acquisition of robot by designing reward based on the concept of intrinsic motivation.

内発的動機づけ

Reservoir Computing for Multi-Objective Switchable Control

For the robot to acquire complex nonlinear dynamics such as human motion, it is effective to have nonlinear dynamics in the controller. We are studying motion control technology utilizing nonlinear dynamics of reservoir computing.

リザーバコンピューティング

Marketings in Large-scale Online Social Networks

We are developing computationally efficient algorithms for locating the seeding nodes having the maximum influence on the outbreak of spreading processes over complex networks, toward achieving effective viral marketings in large-scale online social networks.

口コミ

Network Centralities

We are developing large-scale algorithms for optimally tuning the network centralities (e.g., the PageRank) in complex networks under budget constraints.

中心性

Effectiveness and Optimality of the Bet-hedging Strategy

We are investigating the effectiveness and optimality of the bet-hedging strategy, an intrinsic mechanism of micro bio-populations for surviving through environmental fluctuations, by utilizing the analytical tools from the systems and control theory.

両賭け戦略

System Identification with Manifold Learning

We propose a nonlinear system identification scheme with input-output manifold learning. The scheme is based on a nonlinear dimensionality reduction method regularized by the latent dynamics structure.

入出力多様体学習

Research Equipment

Shadow Hand
Shadow Hand
Barrett
Motion Capture
PEmg Plus
Wireless EMG sensor
Kjunior
Quanser 2DoFArm
Quanser ecp2055d
IP1
LEGO
Computing Machine
baxtersystem
Nextage