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Mingwei Yeoh

dblp:338/9469 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 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 · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › locomotion
amphibious robot locomotion
0.712023
Mobility Analysis of Screw-Based Locomotion and Propulsion in Various Media · ICRA 2023
Robotics › Legged, aerial and field robots
field robotics
0.712023
Mobility Analysis of Screw-Based Locomotion and Propulsion in Various Media · ICRA 2023

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

experimental performance analysis · 0.7
YearPublicationVenuePosition
2023 Mobility Analysis of Screw-Based Locomotion and Propulsion in Various Media
abstract
Robots “in-the-wild” encounter and must traverse widely varying terrain, ranging from solid ground to granular materials like sand to full liquids. Numerous approaches exist, including wheeled and legged robots, each excelling in specific domains. Screw-based locomotion is a promising approach for multi-domain mobility, leveraged in exploratory robotic designs, including amphibious vehicles and snake robotics. However, unlike other forms of locomotion, there is limited exploration of the models, parameter effects, and efficiency for multi-terrain Archimedes screw locomotion. In this work, we present work towards this missing component in understanding screw-based locomotion: comprehensive experimental results and performance analysis across different media. We designed a mobile test bed for indoor and outdoor experimentation to collect this data. Beyond quantitatively showing the multi-domain mobility of screw-based locomotion, we envision future researchers and engineers using the presented results to design effective screw-based locomotion systems.
Jason Lim, Calvin Joyce, Elizabeth Peiros, Mingwei Yeoh, Peter V. Gavrilov, Sara G. Wickenhiser, Dimitri A. Schreiber, Florian Richter 0002, Michael C. Yip
ICRA4