Tetsuya Ogata

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Japan

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Recent Grants

Grant: Close

Acquisition and behavior generation of motion primitives of the robot using a deep learning

Open Date: 2015-04-01

Close Date: 2020-03-31

Grant: Close

Social cognitive development model and the developmental disability support system configuration theory based on it

Open Date: 2012-06-28

Close Date: 2017-03-31

Grant: Close

Prediction Object Dynamics and Tool Handling based on Active Perception of Humanoid Robot

Open Date: 2009-01-01

Close Date: 2012-12-31

Grant: Close

Design Theory for Dynamical Systems with Semiosis

Open Date: 2007-01-01

Close Date: 2011-12-31

Grant: Close

Development of Robot Audition based on Computational Auditory Scene Analysis

Open Date: 2007-01-01

Close Date: 2011-12-31

Articles (11)

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2022

Year:

2022

Year:

2022

Collaborators (3)

Takashi Sato

教授 / Professor

Kyoto University

JAPAN

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Lorenzo Jamone

Lecturer in Robotics

Queen Mary University of London

UNITED KINGDOM

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Hiroki Mori

Associate Professor

Future Robot Organization

JAPAN

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Tetsuya Ogata

Research Interests

Explore related searches

Contact this professor

Recent Grants

Articles (11)

Work Tempo Instruction Framework for Balancing Human Workload and Productivity in Repetitive Task

Uncertainty-Aware Haptic Shared Control With Humanoid Robots for Flexible Object Manipulation

Learning-based collision-free planning on arbitrary optimization criteria in the latent space through cGANs

Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions

Tactile Transfer Learning and Object Recognition With a Multifingered Hand Using Morphology Specific Convolutional Neural Networks

Learning Bidirectional Translation Between Descriptions and Actions With Small Paired Data

Deep Active Visual Attention for Real-Time Robot Motion Generation: Emergence of Tool-Body Assimilation and Adaptive Tool-Use

Robot Task Learning With Motor Babbling Using Pseudo Rehearsal

Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control

Multi-Fingered In-Hand Manipulation With Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensors

Utilization of Image/Force/Tactile Sensor Data for Object-Shape-Oriented Manipulation: Wiping Objects With Turning Back Motions and Occlusion

Collaborators (3)

Takashi Sato

Lorenzo Jamone

Hiroki Mori

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