Evidence map›Paper›PMID 42780103›Full record

ArticleFrontiers in robotics and AI2026

A new integrated hybrid technique for risk assessment in human-robot collaboration.

Kristyna Hamrikova, Daniel Hartmann, Ales Vysocky, Vendula Laciok, Radim Hercik, Ales Bernatik

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 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

6 authors.

Kristyna HamrikovaFaculty of Safety Engineering, VSB - Technical University of Ostrava, Ostrava, Czechia.
Daniel HartmannFaculty of Mechanical Engineering, VSB -Technical University of Ostrava, Ostrava, Czechia.
Ales VysockyFaculty of Mechanical Engineering, VSB -Technical University of Ostrava, Ostrava, Czechia.
Vendula LaciokFaculty of Safety Engineering, VSB - Technical University of Ostrava, Ostrava, Czechia.
Radim HercikFaculty of Electrical Engineering and Computer Science, VSB -Technical University of Ostrava, Ostrava, Czechia.
Ales BernatikFaculty of Safety Engineering, VSB - Technical University of Ostrava, Ostrava, Czechia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-robot collaboration offers new opportunities to increase productivity, flexibility and ergonomics in work processes, however, it also introduces specific risks associated with a shared workspace between humans and robots, for which traditional risk assessment techniques may not be sufficiently effective. This article summarizes selected risk assessment techniques designed for the field of Human-Robot Collaboration (HRC) and evaluates their strengths and weaknesses with respect to their applicability in a collaborative environment. Based on the identified limitations, a new hybrid technique is presented that combines Hierarchical Task Analysis (HTA), Hazard and Operability Study (HAZOP), Process Failure Mode and Effects Analysis (HRC-PFMEA) and Risk matrix. The proposed approach integrates qualitative and quantitative risk assessments, enables risk identification at an early stage of system design, and increases the transparency of work processes. The applicability and logical workflow of the proposed method are demonstrated using a simulation scenario of an assisted assembly workstation created in a digital environment.

Indexed as

collaborative applicationscollaborative robot (cobot)human–robot collaborationoccupational health and safetyrisk assessment

Identifiers

PMID42780103
PMCPMC13597355

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.