Evidence map›Paper›PMID 42817434›Full record

ArticleSensors (Basel, Switzerland)2026

Towards Collaborative Autonomous Operations in Power Infrastructure: A Robotic Fine Manipulation Framework.

Guangda Xu, You Dong

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

2 authors.

Guangda XuDepartment of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.ORCID 0009-0002-9671-1335
You DongDepartment of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.ORCID 0000-0002-2499-0999

Funding

Research Grants Council of the Hong Kong Special Administrative Region R5048-25
6 · The paper itself

Abstract

Gas-insulated substations (GISs) have been widely adopted in modern power systems due to their compact design and high reliability. However, the potential generation of toxic byproducts poses significant risks to manual operations such as gas pressure adjustments, highlighting the necessity for robotic deployments. This paper proposes a Robot Operating System (ROS)-based robotic framework with human-robot collaborative autonomy for GIS operations. The framework employs a 6-degree-of-freedom (6-DOF) robotic arm, integrated with a motion control system for trajectory execution, a visual perception system enhanced by the coordinate attention (CA) mechanism for small-scale detection and localization, and a communication system for data exchange. The framework improves the accuracy of component perception and enables fine manipulation in complex environments, reducing reliance on manual intervention while facilitating a safe collaborative autonomous workflow through dynamic adjustment of autonomy level and control authority. Experimental results on the representative gas pressure adjustment task demonstrate an autonomous operational success rate exceeding 90% under the proposed configuration in dynamic scenarios. By enhancing safety and precision, this study advances robotic solutions for hazardous operations and lays a foundation for broader infrastructure applications.

Indexed as

collaborative autonomyfine manipulationinfrastructure operationrobot operating system (ROS)small-scale component detection

Identifiers

PMID42817434
PMCPMC13611429

What OpenQuestion holds

Textmetadata
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.