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Kazuya Murotani

dblp:234/2589 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
0009-0008-9060-0638ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Legged, aerial and field robots · 62% Motion planning and robot control · 38%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › legged robots
legged robot locomotion
0.412019
Resolved Viscoelasticity Control Considering Singularity for Knee-stretched Walking of a Humanoid · ICRA 2019
Robotics › Motion planning and robot control
singularity handling
0.112019
Resolved Viscoelasticity Control Considering Singularity for Knee-stretched Walking of a Humanoid · ICRA 2019
Robotics › Motion planning and robot control
whole-body control
0.112019
Resolved Viscoelasticity Control Considering Singularity for Knee-stretched Walking of a Humanoid · ICRA 2019

Methods — techniques the papers use, named apart from their topics

viscoelasticity resolution · 0.4resolved viscoelasticity control · 0.4
YearPublicationVenuePosition
2019 Resolved Viscoelasticity Control Considering Singularity for Knee-stretched Walking of a Humanoid
abstract
This paper describes a stable knee-stretched walking of a humanoid by the resolved viscoelasticity control (RVC). The RVC method resolves multiple viscoelasticities in task-space, including the center of mass viscoelasticity for balancing, into joint-space viscoelasticity. Although a robust and compliant motion was achieved by the RVC method in previous studies, the conventional knee-bent posture to avoid the kinematic singularity suffered large knee joint torque. In this study, we propose an extension of the RVC capable of the kinematic singularity. We demonstrate through simulations and experiments that the RVC method considering the singularity achieves a stable and human-like walking, reducing the knee joint torque and improving the energy efficiency.
Kazuya Murotani, Ko Yamamoto 0001, Tianyi Ko, Yoshihiko Nakamura
ICRA1