collaborators

6 papers

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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,…

cs.RO2024

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…

cs.RO2024

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…