Analysis of Collision Types in Collaborative Robots Using Mechanism Actuated by Pneumatic Artificial Muscle

In the safety technology of collaborative robots, standards differentiate between various collision types, the identification and differentiation of which are essential for ensuring safe operation. The objective of this paper is to develop and test a mechanism actuated by artificial muscle to examine the detection of these profiles in different collision scenarios. The ISO 15066 standard distinguishes between two types of collisions: quasi-static and transient. Using a simplified model, experiments were conducted to evaluate whether sensors could identify collision types accurately. The results demonstrate the feasibility of identifying collision types through sensor data. The findings have the potential to enhance the safety of collaborative robots.

Authors

Institutions

Publication Details

Journal
Actuators
Published
2025-01-10
DOI
https://doi.org/10.3390/act14010022
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Collision Types in Collaborative Robots Using Mechanism Actuated by Pneumatic Artificial Muscle

József Sárosi, Dávid Kóczi
Actuators
Modular Robots and Swarm Intelligence
article

Analysis of Collision Types in Collaborative Robots Using Mechanism Actuated by Pneumatic Artificial Muscle

József Sárosi, Dávid Kóczi
article en

Abstract

In the safety technology of collaborative robots, standards differentiate between various collision types, the identification and differentiation of which are essential for ensuring safe operation. The objective of this paper is to develop and test a mechanism actuated by artificial muscle to examine the detection of these profiles in different collision scenarios. The ISO 15066 standard distinguishes between two types of collisions: quasi-static and transient. Using a simplified model, experiments were conducted to evaluate whether sensors could identify collision types accurately. The results demonstrate the feasibility of identifying collision types through sensor data. The findings have the potential to enhance the safety of collaborative robots.

ActuatorsVol. 14(1)
University of Szeged (HU)
Openalex Percentile: Top 99%
Modular Robots and Swarm Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Analysis of Collision Types in Collaborative Robots Using Mechanism Actuated by Pneumatic Artificial Muscle — József Sárosi, Dávid Kóczi · Actuators (2025) | TGRS Research Map | TGRS