66 citations · 135 across the 11 of their papers we have counts for
12 papers · 1 filter
Continuous Manifold-Decomposed Impedance Retargeting for Contact-Rich Imitation Learning
Jiahao Liu, Kento Kawaharazuka, Tasuku Makabe +1
CMDIR extends Manifold-Decomposed Impedance Retargeting (MDIR) to transform fixed-impedance demonstrations into continuous variable-impedance controllers, which can also serve as s…
TRACT: Temporally Routed Action Chunks with Chronological Phase Authority for Contact-Rich Manipulation
Jiahao Liu, Kento Kawaharazuka, Tasuku Makabe +1
Action chunking shortens the effective decision horizon of robot imitation learning by predicting multiple future actions, while conventional phase conditioning describes the curre…
MDIR: A Task-Manifold Impedance Retargeting Method for Contact-Rich Teleoperation
Liu Jiahao, Kento Kawaharazuka, Tasuku Makabe +1
Fixed Cartesian impedance makes contact-rich teleoperation demonstrations practical, but gains that secure progress and contact support also determine impact and force variability.…
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…
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…
A Robot Kinematics Model Estimation Using Inertial Sensors for On-Site Building Robotics
Hiroya Sato, Tasuku Makabe, Iori Yanokura +3
In order to make robots more useful in a variety of environments, they need to be highly portable so that they can be transported to wherever they are needed, and highly storable s…
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…
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…
Five-fingered Hand with Wide Range of Thumb Using Combination of Machined Springs and Variable Stiffness Joints
Shogo Makino, Kento Kawaharazuka, Ayaka Fujii +7
Human hands can not only grasp objects of various shape and size and manipulate them in hands but also exert such a large gripping force that they can support the body in the situa…
Daily Assistive Modular Robot Design Based on Multi-Objective Black-Box Optimization
Kento Kawaharazuka, Tasuku Makabe, Kei Okada +1
The range of robot activities is expanding from industries with fixed environments to diverse and changing environments, such as nursing care support and daily life support. In par…
Online Estimation of Self-Body Deflection With Various Sensor Data Based on Directional Statistics
Hiroya Sato, Kento Kawaharazuka, Tasuku Makabe +2
In this paper, we propose a method for online estimation of the robot's posture. Our method uses von Mises and Bingham distributions as probability distributions of joint angles an…
Design and Control of a Small Humanoid Equipped with Flight Unit and Wheels for Multimodal Locomotion
Kazuki Sugihara, Moju Zhao, Takuzumi Nishio +3
Humanoids are versatile robotic platforms owing to their limbs with multiple degrees of freedom. Although humanoids can walk like humans, they are relatively slow, and cannot run o…