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Yi-Syuan Shen

dblp:242/4395 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

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 · 39% Motion planning and robot control · 30% Robot manipulation · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › force sensing
contact force estimation
0.912025
Contact Force Estimation for a Leg-Wheel Transformable Robot With Varying Contact Points · ICRA 2025
Robotics › Motion planning and robot control › locomotion control
legged robot control
0.912025
Contact Force Estimation for a Leg-Wheel Transformable Robot With Varying Contact Points · ICRA 2025
Robotics › Legged, aerial and field robots › wheel-legged robot
leg-wheel transformable robot
0.912025
Contact Force Estimation for a Leg-Wheel Transformable Robot With Varying Contact Points · ICRA 2025
Robotics › Legged, aerial and field robots › legged robots › legged robot locomotion
quadruped locomotion
0.312025
Contact Force Estimation for a Leg-Wheel Transformable Robot With Varying Contact Points · ICRA 2025

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

virtual work method · 0.9kinematic modeling · 0.9jacobian derivation · 0.9
YearPublicationVenuePosition
2025 Contact Force Estimation for a Leg-Wheel Transformable Robot With Varying Contact Points
abstract
Accurate estimation of contact forces is crucial for effective control of quadrupedal robots, especially in complex locomotion scenarios. In this paper, we introduce a novel force estimation technique for robots equipped with transformable leg-wheels. Unlike conventional methods that focus on forces at specific contact points, our approach expresses varying contact points through a simplified kinematic model and derives the corresponding Jacobian matrices. This allows us to apply the virtual work method to evaluate contact forces across the entire surface of the leg-wheel, including the tips, sides, and other contact regions. This adaptability is particularly advantageous in hybrid locomotion modes, where different parts of the leg-wheel interact with the terrain. The proposed method is highly efficient, relying solely on motor current and position feedback without the need for additional sensors. We validate our approach through simulations and real-world experiments, demonstrating its accuracy, robustness, and applicability under diverse operational conditions.
Yi-Syuan Shen, Wei-Shun Yu, Pei-Chun Lin
ICRA1