73 citations · 778 across the 70 of their papers we have counts for
38 papers · 1 filter
Environmentally Adaptive Control Including Variance Minimization Using Stochastic Predictive Network with Parametric Bias: Application to Mobile Robots
Kento Kawaharazuka, Koki Shinjo, Yoichiro Kawamura +2
In this study, we propose a predictive model composed of a recurrent neural network including parametric bias and stochastic elements, and an environmentally adaptive robot control…
Task-specific Self-body Controller Acquisition by Musculoskeletal Humanoids: Application to Pedal Control in Autonomous Driving
Kento Kawaharazuka, Kei Tsuzuki, Shogo Makino +6
The musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex flexible body is difficult. Although we have developed an online acquisition…
Modification of muscle antagonistic relations and hand trajectory on the dynamic motion of Musculoskeletal Humanoid
Yuya Koga, Kento Kawaharazuka, Moritaka Onitsuka +6
In recent years, some research on musculoskeletal humanoids is in progress. However, there are some challenges such as unmeasurable transformation of body structure and muscle path…
Design of a Five-Fingered Hand with Full-Fingered Tactile Sensors Using Conductive Filaments and Its Application to Bending after Insertion Motion
Kazuhiro Miyama, Shun Hasegawa, Kento Kawaharazuka +3
The purpose of this study is to construct a contact point estimation system for the both side of a finger, and to realize a motion of bending the finger after inserting the finger…
Motion Modification Method of Musculoskeletal Humanoids by Human Teaching Using Muscle-Based Compensation Control
Kento Kawaharazuka, Yuya Koga, Manabu Nishiura +5
While musculoskeletal humanoids have the advantages of various biomimetic structures, it is difficult to accurately control the body, which is challenging to model. Although variou…
Adaptive Body Schema Learning System Considering Additional Muscles for Musculoskeletal Humanoids
Kento Kawaharazuka, Akihiro Miki, Yasunori Toshimitsu +2
One of the important advantages of musculoskeletal humanoids is that the muscle arrangement can be easily changed and the number of muscles can be increased according to the situat…
Self-Body Image Acquisition and Posture Generation with Redundancy using Musculoskeletal Humanoid Shoulder Complex for Object Manipulation
Yuya Koga, Kento Kawaharazuka, Yasunori Toshimitsu +6
We proposed a method for learning the actual body image of a musculoskeletal humanoid for posture generation and object manipulation using inverse kinematics with redundancy in the…
Component Modularized Design of Musculoskeletal Humanoid Platform Musashi to Investigate Learning Control Systems
Kento Kawaharazuka, Shogo Makino, Kei Tsuzuki +8
To develop Musashi as a musculoskeletal humanoid platform to investigate learning control systems, we aimed for a body with flexible musculoskeletal structure, redundant sensors, a…
Dynamic Cloth Manipulation Considering Variable Stiffness and Material Change Using Deep Predictive Model with Parametric Bias
Kento Kawaharazuka, Akihiro Miki, Masahiro Bando +2
Dynamic manipulation of flexible objects such as fabric, which is difficult to modelize, is one of the major challenges in robotics. With the development of deep learning, we are b…
Robust Continuous Motion Strategy Against Muscle Rupture using Online Learning of Redundant Intersensory Networks for Musculoskeletal Humanoids
Kento Kawaharazuka, Manabu Nishiura, Yasunori Toshimitsu +5
Musculoskeletal humanoids have various biomimetic advantages, of which redundant muscle arrangement is one of the most important features. This feature enables variable stiffness c…
Human-mimetic binaural ear design and sound source direction estimation for task realization of musculoskeletal humanoids
Yusuke Omura, Kento Kawaharazuka, Yuya Nagamatsu +7
Human-like environment recognition by musculoskeletal humanoids is important for task realization in real complex environments and for use as dummies for test subjects. Humans inte…
Antagonist Inhibition Control in Redundant Tendon-driven Structures Based on Human Reciprocal Innervation for Wide Range Limb Motion of Musculoskeletal Humanoids
Kento Kawaharazuka, Masaya Kawamura, Shogo Makino +3
The body structure of an anatomically correct tendon-driven musculoskeletal humanoid is complex, and the difference between its geometric model and the actual robot is very large b…
Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids
Kento Kawaharazuka, Manabu Nishiura, Yuya Koga +6
For a robot with redundant sensors and actuators distributed throughout its body, it is difficult to construct a controller or a neural network using all of them due to computation…
Human Mimetic Forearm Design with Radioulnar Joint using Miniature Bone-Muscle Modules and Its Applications
Kento Kawaharazuka, Shogo Makino, Masaya Kawamura +4
The human forearm is composed of two long, thin bones called the radius and the ulna, and rotates using two axle joints. We aimed to develop a forearm based on the body proportion,…
Imitation Learning with Additional Constraints on Motion Style using Parametric Bias
Kento Kawaharazuka, Yoichiro Kawamura, Kei Okada +1
Imitation learning is one of the methods for reproducing human demonstration adaptively in robots. So far, it has been found that generalization ability of the imitation learning e…
Estimation and Control of Motor Core Temperature with Online Learning of Thermal Model Parameters: Application to Musculoskeletal Humanoids
Kento Kawaharazuka, Naoki Hiraoka, Kei Tsuzuki +5
The estimation and management of motor temperature are important for the continuous movements of robots. In this study, we propose an online learning method of thermal model parame…
Adaptive Robotic Tool-Tip Control Learning Considering Online Changes in Grasping State
Kento Kawaharazuka, Kei Okada, Masayuki Inaba
Various robotic tool manipulation methods have been developed so far. However, to our knowledge, none of them have taken into account the fact that the grasping state such as grasp…
Object Recognition, Dynamic Contact Simulation, Detection, and Control of the Flexible Musculoskeletal Hand Using a Recurrent Neural Network with Parametric Bias
Kento Kawaharazuka, Kei Tsuzuki, Moritaka Onitsuka +4
The flexible musculoskeletal hand is difficult to modelize, and its model can change constantly due to deterioration over time, irreproducibility of initialization, etc. Also, for…
Stable Tool-Use with Flexible Musculoskeletal Hands by Learning the Predictive Model of Sensor State Transition
Kento Kawaharazuka, Kei Tsuzuki, Moritaka Onitsuka +4
The flexible under-actuated musculoskeletal hand is superior in its adaptability and impact resistance. On the other hand, since the relationship between sensors and actuators cann…
Musculoskeletal AutoEncoder: A Unified Online Acquisition Method of Intersensory Networks for State Estimation, Control, and Simulation of Musculoskeletal Humanoids
Kento Kawaharazuka, Kei Tsuzuki, Moritaka Onitsuka +4
While the musculoskeletal humanoid has various biomimetic benefits, the modeling of its complex structure is difficult, and many learning-based systems have been developed so far.…
Toward Autonomous Driving by Musculoskeletal Humanoids: A Study of Developed Hardware and Learning-Based Software
Kento Kawaharazuka, Kei Tsuzuki, Yuya Koga +9
This paper summarizes an autonomous driving project by musculoskeletal humanoids. The musculoskeletal humanoid, which mimics the human body in detail, has redundant sensors and a f…
Design, Control, and Motion-Planning for a Root-Perching Rotor-Distributed Manipulator
Takuzumi Nishio, Moju Zhao, Kei Okada +1
Manipulation performance improvement is crucial for aerial robots. For aerial manipulators, the baselink position and attitude errors directly affect the precision at the end effec…
Online Learning Feedback Control Considering Hysteresis for Musculoskeletal Structures
Kento Kawaharazuka, Kei Okada, Masayuki Inaba
While the musculoskeletal humanoid has various biomimetic benefits, its complex modeling is difficult, and many learning control methods have been developed. However, for the actua…
Learning of Balance Controller Considering Changes in Body State for Musculoskeletal Humanoids
Kento Kawaharazuka, Yoshimoto Ribayashi, Akihiro Miki +4
The musculoskeletal humanoid is difficult to modelize due to the flexibility and redundancy of its body, whose state can change over time, and so balance control of its legs is cha…