Evidence map›Paper›PMID 41600290›Full record

ArticleSensors (Basel, Switzerland)2026

Research on Robot Collision Response Based on Human-Robot Collaboration.

Sicheng Zhong, Chaoyang Xu, Guoqiang Chen, Yanghuan Xu, Zhijun Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Sicheng ZhongCollege of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China.
Chaoyang XuCollege of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China.
Guoqiang ChenCollege of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China.
Yanghuan XuCollege of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China.
Zhijun WangCollege of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China.ORCID 0000-0003-3316-4821

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid advancement of science and technology, robotics is evolving towards more profound and extensive applications. Nevertheless, the inherent limitations of traditional industrial "caged" robots have significantly impeded the full utilization of their capabilities. Consequently, breaking free from these constraints and realizing human-robot collaboration has emerged as a new developmental trend in the robotics field. The collision-response mechanism, as a crucial safeguard for human-robot collaboration safety, has become a pivotal issue in enhancing the performance of human-robot interaction. To address this, an adaptive admittance control collision-response algorithm is proposed in this paper, grounded in the principle of admittance control. A collision simulation model of the AUBO-i5 collaborative robot is constructed. The effectiveness of the proposed algorithm is verified through simulation experiments focusing on both the end-effector collision and body collision of the robot, and by comparing it with existing admittance control algorithms. Furthermore, a collision-response experimental platform is established based on the AUBO-i5 collaborative robot. Experimental studies on end-effector and body collisions are conducted, providing practical validation of the reliability and utility of the proposed adaptive admittance control collision-response algorithm.

Indexed as

Man-Machine SystemsRoboticsAlgorithmsComputer SimulationCooperative BehaviorHumansadaptive conductance controlcollision corresponding algorithmscollision responsehuman-robot collaboration

Identifiers

PMID41600290
PMCPMC12846152

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.