Replication Data for: Real-time capable feedrate optimization for laser processes with redundant axes via two-stage regularized linear programming

DOI

Simulation and experimental dataset for feedrate planning in redundant-axis laser machines.

This dataset belongs to the Open Access publication "Real-time capable feedrate optimization for laser processes with redundant axes via two-stage regularized linear programming" (doi: 10.1016/j.ijmachtools.2025.104342) A detailed description of the setup can be found in the publication.

The dataset contains the following folders (Feel free to contact the dataset owner if you have any questions about the dataset.):

Simulation - Section 4_1 Simulation results in section 4.1 of the paper, showing the feasibility and computational requirements.

Simulation - Section 4_2 Simulation results in section 4.2 of the paper, comparing the time optimality of different planning methods.

Simulation - Section 4_3 Simulation results in section 4.3 of the paper, analyzing the motion smoothness achieved by numerical regularization.

Experiments - Section 4_4 Experimental results in section 4.4 of the paper, validating the planning algorithms on the test benches compared to the industrial CNC kernel.

Simulation - Section 4_5 Simulation results in section 4.5 of the paper, comparing the presented method with the state of the art.

Videos Illustrative animation of the presented algorithm and recorded videos of the laser engraving experiments.

Identifier
DOI https://doi.org/10.18419/DARUS-4856
Related Identifier IsSupplementTo https://doi.org/10.1016/j.ijmachtools.2025.104342
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-4856
Provenance
Creator Xu, Haijia ORCID logo
Publisher DaRUS
Contributor Xu, Haijia
Publication Year 2025
Funding Reference DFG 557218129
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Xu, Haijia (University of Stuttgart); Xu, Haijia
Representation
Resource Type Dataset
Format application/octet-stream; text/tab-separated-values; video/mp4; application/x-netcdf; application/zip; text/plain
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Version 1.0
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences