Evidence map›Paper›PMID 38616914›Full record

ReviewCyborg and bionic systems (Washington, D.C.)2022

A Survey on Design, Actuation, Modeling, and Control of Continuum Robot.

Jingyu Zhang, Qin Fang, Pingyu Xiang, Danying Sun, Yanan Xue, Rui Jin, Ke Qiu, Rong Xiong, Yue Wang, Haojian Lu

Abstract readReview
In one paragraph

Review in Cyborg and bionic systems (Washington, D.C.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Hybrid-Driven Origami Gripper with Variable Stiffness and Finger Length.Cyborg and bionic systems (Washington, D.C.) · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. A Versatile Continuum Gripping Robot with a Concealable Gripper.Cyborg and bionic systems (Washington, D.C.) · 2023
    Article
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

10 authors.

Jingyu ZhangState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Qin FangState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Pingyu XiangState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Danying SunState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Yanan XueState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Rui JinState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Ke QiuState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Rong XiongState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Yue WangState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.
Haojian LuState Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou 310027, China.ORCID https://orcid.org/0000-0002-1393-3040

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we describe the advances in the design, actuation, modeling, and control field of continuum robots. After decades of pioneering research, many innovative structural design and actuation methods have arisen. Untethered magnetic robots are a good example; its external actuation characteristic allows for miniaturization, and they have gotten a lot of interest from academics. Furthermore, continuum robots with proprioceptive abilities are also studied. In modeling, modeling approaches based on continuum mechanics and geometric shaping hypothesis have made significant progress after years of research. Geometric exact continuum mechanics yields apparent computing efficiency via discrete modeling when combined with numerical analytic methods such that many effective model-based control methods have been realized. In the control, closed-loop and hybrid control methods offer great accuracy and resilience of motion control when combined with sensor feedback information. On the other hand, the advancement of machine learning has made modeling and control of continuum robots easier. The data-driven modeling technique simplifies modeling and improves anti-interference and generalization abilities. This paper discusses the current development and challenges of continuum robots in the above fields and provides prospects for the future.

Identifiers

PMID38616914
PMCPMC11014731

What OpenQuestion holds

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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.