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Wenlong Cui

dblp:366/7373 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 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
Motion planning and robot control · 60% Legged, aerial and field robots · 40%
Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
field robotics
0.912025
Biomimetic Underwater Soft Snake Robot: Self-Motion Sensing and Online Gait Control · IEEE Trans. Robotics 2025
Robotics › Motion planning and robot control › robot control
gait control
0.912025
Biomimetic Underwater Soft Snake Robot: Self-Motion Sensing and Online Gait Control · IEEE Trans. Robotics 2025
Robotics › Motion planning and robot control › robot control › learning control
iterative learning control
0.912025
Biomimetic Underwater Soft Snake Robot: Self-Motion Sensing and Online Gait Control · IEEE Trans. Robotics 2025
Robotics › Motion planning and robot control
robot control
0.912025
Biomimetic Underwater Soft Snake Robot: Self-Motion Sensing and Online Gait Control · IEEE Trans. Robotics 2025
Robotics › Legged, aerial and field robots
underwater robotics
0.912025
Biomimetic Underwater Soft Snake Robot: Self-Motion Sensing and Online Gait Control · IEEE Trans. Robotics 2025

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

iterative learning control · 1.7
YearPublicationVenuePosition
2025 Biomimetic Underwater Soft Snake Robot: Self-Motion Sensing and Online Gait Control
abstract
This study draws inspiration from the locomotion and adaptability of aquatic snakes to develop an innovative soft-bodied, hydraulic-driven untethered underwater snake robot “BaiLong.” The robot consists of a segmented soft structure and embeds actuation, control, and power modules in the head. Featuring the self-shape perception capability, it leverages an online iterative learning control method to effectively mitigate body shape deformation errors and attain precise gait movements. As a result, the soft robot has achieved movements emulating the serpentine motion of real snakes with locomotion consistency equivalent to rigid robots. Extensive experiments in both artificial and natural aquatic environments have presented improved swimming speed among soft snakes with promising turning agility, and revealed the gait parameter influence on the linear velocity described by a near-constant Strouhal number. The reported investigation sufficiently demonstrates the swimming feasibility and performance of underwater soft snake robots and significantly advances their capabilities for long-range applications.
Yali Meng, Wenlong Cui, Meng Rao, Yangmin Xie
IEEE Trans. Robotics3