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Record W4410810694 · doi:10.1115/1.4068764

Cost Effective Design and Development of a Cable-Driven Parallel Robot for Concrete Printing

2025· article· en· W4410810694 on OpenAlexaff
Ishan Chawla, Pushparaj Mani Pathak, Qingguo Li

Bibliographic record

VenueASME Letters in Translational Robotics · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsQueen's University
FundersMinistry of Education, India
KeywordsDevelopment (topology)3D printingComputer scienceRobotEngineering drawingConstruction engineeringEngineeringMechanical engineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Abstract Cable-driven parallel robots (CDPRs) are well known for their large workspace and simple design. They are also easy to transport, assemble and disassemble, and more easily reconfigurable. These properties make them a potential alternative for on-site printing of structures. This work presents the detailed steps for the cost-effective design and development of the CDPR for concrete printing. The cost-effectiveness of the design is ensured by using prefabricated materials/parts available in the local market and reducing the machining cost as much as possible. The robot consists of a mobile platform whose position and orientation are controlled by varying cable lengths by the application of winches. A screw extruder is mounted on the mobile platform to extrude concrete/clay. The controller design for the whole system is detailed, and the measures to obtain the trajectory for printing are discussed. Thereafter, the cost analysis of the entire robot is performed. Finally, experimental results are presented to validate the accuracy of the robot.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.260
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueASME Letters in Translational RoboticsSame topicInnovations in Concrete and Construction MaterialsFrench-language works237,207