Limited mobility grasps for fixtureless assembly
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
A novel approach to grasping with an end effector for the purposes of fixtureless assembly is presented. The grasping strategy is based on having the final position of the contacts determined by specific regions of the object geometry. The fingers are placed within limited spaces of the object and moved using frictionless contacts until motion ceases. The limited spaces usually take the form of concave edges or holes in the object. This strategy allows the positioning error to be determined by the accuracy of the part and is independent of the accuracy of the robotic manipulator. A new method for finding form closure is introduced based on maximizing the distances between contacts. The grasping strategy allows deterministic positioning of the object and also provides a means of convergence to these holding points. Testing was done in the plane with three fingers for several cases to show the sensitivity of the grasps to part geometry. The results show the position error is dependent on local shape and was reduced from 1 mm to 0.1 mm for several cases.
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) | 0.001 | 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