66 citations · 405 across the 29 of their papers we have counts for
29 papers
Stability Recognition with Active Vibration for Bracing Behaviors and Motion Extensions Using Environment in Musculoskeletal Humanoids
Kento Kawaharazuka, Manabu Nishiura, Shinsuke Nakashima +7
Although robots with flexible bodies are superior in terms of the contact and adaptability, it is difficult to control them precisely. On the other hand, human beings make use of t…
Reflex-based Motion Strategy of Musculoskeletal Humanoids under Environmental Contact Using Muscle Relaxation Control
Kento Kawaharazuka, Kei Tsuzuki, Moritaka Onitsuka +6
The musculoskeletal humanoid can move well under environmental contact thanks to its body softness. However, there are few studies that actively make use of the environment to rest…
Online Learning of Danger Avoidance for Complex Structures of Musculoskeletal Humanoids and Its Applications
Kento Kawaharazuka, Naoki Hiraoka, Yuya Koga +6
The complex structure of musculoskeletal humanoids makes it difficult to model them, and the inter-body interference and high internal muscle force are unavoidable. Although variou…
Applications of Stretch Reflex for the Upper Limb of Musculoskeletal Humanoids: Protective Behavior, Postural Stability, and Active Induction
Kento Kawaharazuka, Yuya Koga, Kei Tsuzuki +5
The musculoskeletal humanoid has various biomimetic benefits, and it is important that we can embed and evaluate human reflexes in the actual robot. Although stretch reflex has bee…
Exceeding the Maximum Speed Limit of the Joint Angle for the Redundant Tendon-driven Structures of Musculoskeletal Humanoids
Kento Kawaharazuka, Yuya Koga, Kei Tsuzuki +5
The musculoskeletal humanoid has various biomimetic benefits, and the redundant muscle arrangement is one of its most important characteristics. This redundancy can achieve fail-sa…
Design Optimization of Musculoskeletal Humanoids with Maximization of Redundancy to Compensate for Muscle Rupture
Kento Kawaharazuka, Yasunori Toshimitsu, Manabu Nishiura +6
Musculoskeletal humanoids have various biomimetic advantages, and the redundant muscle arrangement allowing for variable stiffness control is one of the most important. In this stu…
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…
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…
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…
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,…
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…
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…
A Method of Joint Angle Estimation Using Only Relative Changes in Muscle Lengths for Tendon-driven Humanoids with Complex Musculoskeletal Structures
Kento Kawaharazuka, Shogo Makino, Masaya Kawamura +3
Tendon-driven musculoskeletal humanoids typically have complex structures similar to those of human beings, such as ball joints and the scapula, in which encoders cannot be install…
TWIMP: Two-Wheel Inverted Musculoskeletal Pendulum as a Learning Control Platform in the Real World with Environmental Physical Contact
Kento Kawaharazuka, Tasuku Makabe, Shogo Makino +8
By the recent spread of machine learning in the robotics field, a humanoid that can act, perceive, and learn in the real world through contact with the environment needs to be deve…
Online Learning of Joint-Muscle Mapping Using Vision in Tendon-driven Musculoskeletal Humanoids
Kento Kawaharazuka, Shogo Makino, Masaya Kawamura +3
The body structures of tendon-driven musculoskeletal humanoids are complex, and accurate modeling is difficult, because they are made by imitating the body structures of human bein…