In-situ Robotic Construction: A Technological Approach to Housing Affordability
Bibliographic record
Abstract
Housing supply challenges are looming large, with estimates suggesting a need for 2 billion new homes over the next 80 years to accommodate a growing global population. Governments, including Canada, are striving to address this issue through ambitious housing development initiatives, but the complexity of the problem calls for more than just policy strategies. To meet such targets, radical and fundamental shifts are required across all stages of design and construction. This paper introduces a technological approach to housing through the development of a cable-driven parallel robot (CDPR) as an innovative and alternative method for in-situ construction. CDPRs have the potential to transform current methods of construction, by eliminating the requirement for highly skilled labor, minimizing waste, and significantly reducing costs and construction timelines. Through a cross- disciplinary collaboration between engineering science and architecture, this paper presents the research conducted towards the development of a functional prototype, one that is highly flexible, portable and modular ensuring the provision of a physical platform for construction. As architecture continues to be bound by outdated methods and high costs of construction, bold technological explorations are required to unlock new territories in delivering affordable and accessible housing, representing a significant step toward a future where housing supply can keep pace with the ever-growing population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".