Evidence map›Paper›PMID 41892139›Full record

ReviewBiomimetics (Basel, Switzerland)2026

Deep-Sea Biomimetic Manta Ray Robots: A Comprehensive Review Based on Operational Depth Spectrum, Structures, Energy Optimization, and Control Systems.

Lugang Ye, Hongyuan Liu, Qiulin Ding, Zhongming Hu, Weikun Li, Weicheng Cui, Dixia Fan

Abstract readReview
In one paragraph

Review in Biomimetics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lugang YeDepartment of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou 310030, China.
Hongyuan LiuDepartment of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou 310030, China.ORCID 0009-0007-0168-0510
Qiulin DingDepartment of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou 310030, China.ORCID 0009-0005-7286-1904
Zhongming HuCollege of Building Eneineering, Huanghuai University, Zhumadian 463000, China.
Weikun LiDepartment of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou 310030, China.ORCID 0000-0002-5262-5235
Weicheng CuiDepartment of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou 310030, China.ORCID 0000-0003-1871-2658
Dixia FanDepartment of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou 310030, China.

Funding

National Natural Science Foundation of China 52401393
6 · The paper itself

Abstract

As deep-sea exploration transitions from large-scale search to precision pinpoint operations, the inherent limitations of traditional "rigid-body and propeller" vehicles-specifically in low-speed maneuverability, environmental compliance, and acoustic stealth-are becoming increasingly apparent. Leveraging its unique integrated "gliding-flapping" locomotion and exceptional maneuverability, the manta ray serves as an ideal biological prototype for next-generation deep-sea operational platforms. From a systems engineering perspective, this paper provides a comprehensive review of the current research status and technical evolution of biomimetic manta ray submersibles. First, a technical pedigree centered on "operational depth" is established, illustrating how design paradigms transition from "mechanism replication" in shallow waters to "pressure adaptation" at full-ocean depths. Second, the mechanical challenges in structural design are explored, demonstrating that a "rigid-flexible" gradient distribution strategy is critical to resolving the conflict between pressure resistance and propulsive compliance. Regarding energy and propulsion, the synergistic effects of hybrid gliding-flapping drives and integrated structural batteries in enhancing long-range endurance and energy efficiency are analyzed. Finally, the evolution of motion control architectures-transitioning from spinal-cord-inspired Central Pattern Generator (CPG) rhythmic control to Deep Reinforcement Learning (DRL) featuring embodied intelligence-is outlined.

Indexed as

bio-inspired submersiblebiomimetic propulsionfull-ocean-depthmanta ray

Identifiers

PMID41892139
PMCPMC13024092

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.