Motion planning for the mobile servicing system in a repair task in the international space station
Bibliographic record
Abstract
The Canadian Mobile Servicing System (MSS) is a 22 DOF robot system that is composed of a base, the SSRMS (Space Station Remote Manipulator System) and SPDM (Special Purpose Dexterous Manipulator System).Current motion planning for MSS is divided into two separate phases: posture planning and path planning.Posture planning is done by trial-and-error, which is highly human-involved and labor-intensive.This thesis treats the two separate phases above as one integrated problem, and develops automatic off-line motion planning methods for MSS to perform repair tasks in the International Space Station, while guaranteeing that the worksite of the manipulators are visible to various cameras mounted on MSS.We modified existing algorithms to take into account camera constraints, and improved some algorithms to speed up the planning process.These automated methods can solve motion planning for MSS in most tasks in about thirty minutes, leading to great savings in time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.005 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".