Load cell torques and force data collection during tele-operated robotic gas tungsten arc welding in presence of collisions
Open accessAbstract
Torque and force signals data were acquired from a load-cell sensor during a robotic welding process, in presence of collisions between the tool and the workpiece edges outlined in part in "Haptic-based touch detection for collaborative robots in welding applications" [1]. The dataset is composed from 15 tests captured during a tele-operated welding robot performing a 1G ASME/AWS (i.e., PA ISO) welding process. The raw data files have been provided. These data can be used to correlate torque signal features with collision events, to improve algorithms of collision detection/avoidance and to develop reliable real-time haptic feedback to the welder. This dataset can also be used to study the torque signal variation in different welding positions (e.g., 2G, 3G, 2F, etc.). Dataset is provided as raw data and in MATLAB files.
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The contamination level of the dataset influences the performance of the algorithm.
“Results confirmed the influence of the contamination level related to the dataset.”
From Advanced Applications of Industrial Robotics: New Trends and Possibilities (2021) · cites this paper as [25]
The Data description section (page unavailable) describes raw welding measurements and collision labels, while Value of the data says the dataset could be used to develop algorithms. Neither reports algorithm-performance results or addresses dataset contamination levels (searched: contamination level, outliers, noise, algorithm performance). (LLM, conf=0.74)
Experimental — accuracy not yet measuredThe 3-Sigma rule achieved better performance than the Hampel identifier in precision percentage (mean 99.9%) and miss rate (mean 10%).
“Experimental results showed better performance of the 3-Sigma rule in terms of precision percentage (mean value of 99.9%) and miss rate (mean value of 10%) concerning the Hampel identifier.”
From Advanced Applications of Industrial Robotics: New Trends and Possibilities (2021) · cites this paper as [25]
The Data description presents a raw dataset from 15 welding tests, and Value of the data says it could be used to develop collision-detection algorithms. Neither section reports a comparison of the 3-Sigma rule with the Hampel identifier. Searches for those methods and for the stated 99.9% precision and 10% miss rate found no matching results in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Advanced Applications of Industrial Robotics: New Trends and Possibilities
Dzedzickis, A., Subačiūtė-Žemaitienė, J., Šutinys, E., Samukaitė-Bubnienė, U., & Bučinskas, V. (2021) · Applied Sciences · doi:10.3390/app12010135 · Cited by 228 · see citing works
- Authors
- Tannous, M., Bologna, F., & Stefanini, C.
- Affiliations
- Scuola Superiore Sant'Anna (IT)
- Corresponding author
- Tannous, Michael
- Bologna, Francesco
- Venue
- Data in Brief
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 31
- Pages
- 105981
- ISSN
- 2352-3409 (ISSN-L)
- PMC
- PMC7364114
- OpenAlex
- W3004736846
- Cited by
- 5
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2021: 2
- Type
- data paper
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Data in Brief (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- CINECA IRIS Institutional Research Information System (Sant'Anna School of Advanced Studies) (submittedVersion)
- Funders
- Scuola Superiore Sant'Anna
- Regione Toscana
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Teleoperation and Haptic Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Physical Sciences › Engineering › Mechanical Engineering › Welding Techniques and Residual Stresses
- Keywords
- teleoperation, collision detection, collision avoidance, torque signals, force signals, load cell sensor, haptic feedback, collaborative robots, welding position
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