Evidence map›Paper›PMID 35370590›Full record

ArticleFrontiers in neurorobotics2022

A Cooperative Shared Control Scheme Based on Intention Recognition for Flexible Assembly Manufacturing.

Guangbing Zhou, Jing Luo, Shugong Xu, Shunqing Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Guangbing ZhouSchool of Information and Communication Engineering, Shanghai University, Shanghai, China.
Jing LuoSchool of Automation, Wuhan University of Technology, Wuhan, China.
Shugong XuSchool of Information and Communication Engineering, Shanghai University, Shanghai, China.
Shunqing ZhangSchool of Information and Communication Engineering, Shanghai University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-robot collaboration (HRC) has been widely utilized in industrial manufacturing and requires a human to cooperate with a robot at the same workspace. However, as HRC focuses on workspace sharing along with independent work, it is not a real collaboration between a human and a robot and, thus, cannot guarantee a smooth cooperation and synchronous operation. To this end, a cooperative shared control scheme based on intention recognition is proposed in this study by sharing workspace and time. In the proposed method, a classification algorithm based on three-dimensional (3D) point cloud is utilized to recognize the human operation intention. Then, the robot can select a suitable tool to match the human's operation. A robot motion control algorithm is developed to detect the obstacles in the HRC process. A cooperative control strategy is introduced to achieve synchronous operation. A simple assembly task is also performed to demonstrate the proposed scheme's effectiveness. The proposed HRC method with shared control can be extended to more complicated and delicate flexible tasks in assembly manufacturing.

Indexed as

assembly taskcooperative shared controlhuman-robot collaborationintention recognitionobstacle avoidance

Identifiers

PMID35370590
PMCPMC8967170

What OpenQuestion holds

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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.