Collaborative timber joint assembly: Augmented reality for multi-level human-robot interaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research introduces an innovative Augmented Reality (AR) workflow for Human-Robot Interaction (HRI) in timber construction. The approach leverages human dexterity and adaptability alongside the strength and precision of robotic arms to assemble timber structures connected by wood-wood connections. While research in the field of automated construction generally focuses on singular interactions, such as robot agents carrying components and human agents attaching them, this paper explores multiple degrees of interaction involving cooperation or collaboration between agents. A new algorithmic framework is developed to automate the generation of holographic instructions and allocate assembly tasks to human and robot agents according to their abilities. The application to a full-scale demonstrator reveals that certain elements necessitate collaboration for assembly, while others can exclusively be assembled manually or robotically. Ultimately, the research also highlights the benefits of AR in assisting manual assembly, simulating robot trajectories, and increasing safety during collaborative tasks.
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.
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 it