Evidence map›Paper›PMID 31241408›Full record

ArticleSoft robotics2019

Fiber Optic Shape Sensing for Soft Robotics.

Kevin C Galloway, Yue Chen, Emily Templeton, Brian Rife, Isuru S Godage, Eric J Barth

Abstract read
In one paragraph

Article in Soft robotics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Trial
  2. Review
  3. RoboticERJ open research · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Toward Autonomous Self-Healing in Soft Robotics: A Review and Perspective for Future Research.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2025
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Sensing of Continuum Robots: A Review.Sensors (Basel, Switzerland) · 2024
    Review
  13. Review
  14. Integrated Actuation and Sensing: Toward Intelligent Soft Robots.Cyborg and bionic systems (Washington, D.C.) · 2024
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors.

Kevin C GallowayDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee.
Yue ChenDepartment of Mechanical Engineering, University of Arkansas, Fayetteville, Arkansas.
Emily TempletonLuna Innovations, Inc., Blacksburg, Virginia.
Brian RifeLuna Innovations, Inc., Blacksburg, Virginia.
Isuru S GodageSchool of Computing, DePaul University, Chicago, Illinois.
Eric J BarthDepartment of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While soft material actuators can undergo large deformations to execute very complex motions, what is critically lacking in soft material robotic systems is the ability to collect high-resolution shape information for sophisticated functions such as environmental mapping, collision detection, and full state feedback control. This work explores the potential of a nearly commercial fiber optic shape sensor (FOSS) and presents the first demonstrations of a monolithic, multicore FOSS integrated into the structure of a fiber-reinforced soft actuator. In this pilot study, we report an open loop sensorized soft actuator capable of submillimeter position feedback that can detect the soft actuator's shape, environmental shapes, collision locations, and material stiffness properties.

Indexed as

fiber optic shape sensorsoft actuatorsoft roboticssoft sensor

Identifiers

PMID31241408
PMCPMC6786339

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.