Evidence map›Paper›PMID 38606005›Full record

ArticleIEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society2018

Comparative Peg-in-Hole Testing of a Force-Based Manipulation Controlled Robotic Hand.

Karl Van Wyk, Mark Culleton, Joe Falco, Kevin Kelly

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
7.9field-weighted citation impact, top 2% of its field
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

4 citing papers in PubMed, 100 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Efficiently Improving and Quantifying Robot Accuracy In Situ.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2019
    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

4 authors at 2 institutions in 2 countries.

Karl Van WykNational Institute of Standards and Technology, Gaithersburg, MD 20899 USA.ORCID 0000-0001-5535-949X
Mark CulletonDepartment of Mechanical and Manufacturing Engineering, Trinity College Dublin, Dublin 2, Ireland.ORCID 0000-0002-5545-753X
Joe FalcoNational Institute of Standards and Technology, Gaithersburg, MD 20899 USA.ORCID 0000-0002-7794-5331
Kevin KellyDepartment of Mechanical and Manufacturing Engineering, Trinity College Dublin, Dublin 2, Ireland.ORCID 0000-0003-2939-2274
National Institute of Standards and Technology · USTrinity College Dublin · IE

Funding

Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

Force-based manipulation control strategies are evolving as a primary mechanism in robotics for performing the fine manipulation tasks typical within manufacturing assembly. The ability to systematically compare robotic system performance and quantify true advancement in fine manipulation is of utmost importance. Accordingly, the objectives of this paper are threefold: 1) creation of a peg-in-hole test method with associated performance metrics and a systematic data analysis strategy for performance benchmarking, 2) first demonstration of a recently developed manipulation controller piloting a robotic hand and its paired task-level logic for completing the peg-in-hole test, and 3) exemplifying the performance benchmarking technique by comparing two approaches for robotic insertions-the previously mentioned compliant hand, stiff arm system, and a stiff gripper, compliant arm system. Analyses reveal that the unconventional hand system can perform at and sometimes above the level of the gripper system in the developed peg-in-hole scenario. Moreover, the hand's active control of the peg's full Cartesian pose reduces positional error sensitivity and minimizes exerted insertion forces, highlighting the strategy's potential for fine manipulation tasks. Results indicate that robotic arms equipped with highly articulated and sensorized robotic hands can provide a truly realizable solution path for performing peg-in-hole tasks.

Indexed as

Graspingmanipulationperformance testing

Identifiers

PMID38606005
PMCPMC11008496
OpenAlexW2793264449

What OpenQuestion holds

Textmetadata
LicenceTDM
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.