Results of Human-in-the-Loop Testing of the Force/Moment Accommodation Feature using the Special Purpose Dexterous Manipulator Ground Test Bed
Bibliographic record
Abstract
The Special Purpose Dexterous Manipulator (SPDM) is part of Canada's contribution to the International Space Station. Crew members inside the pressurized volume will command this dexterous robot to perform maintenance operations on the station that are normally associated with Extra-Vehicular Activities (EVA's). Operations will include complex tasks such as the replacement of faulty electronics units and battery boxes, collectively called Orbital Replaceable Units (ORUs). This type of task requires a manipulator that precisely controls and regulates contact forces. Precision is necessary to sense and correct for positional misalignments during the insertion of ORUs as well as to prevent jamming and overloading the ORU and worksite. The SPDM employs a feature called Force/Moment Accommodation (FMA), which is the robotic analogue of the crew member's sense of touch and muscle response, to actively regulate or accommodate the forces and moments generated during contact operations in all six degrees of freedom. This feature allows the robot to handle the fine alignment function during an ORU insertion task without operator input. The FMA feature has been demonstrated on the SPDM Ground Test Bed (SPDM GT), a gravity compensated robotic arm that is functionally and dynamically equivalent to the flight SPDM arm. An international crew evaluation of the berthing task using two types of flight ORUs and the SPDM GT was conducted. Trials with and without FMA active show that FMA significantly reduces operator workload and timeline. In addition, FMA enables the operator to perform robotic tasks that are not possible without this type of automatic control feature. The crew rated the ORU insertion task a 1 on the Cooper-Harper scale (excellent) when FMA was active, and rated the task between 6 and 9 (poor) when FMA was disabled. The trials have confirmed that the SPDM with FMA enabled is a capable, flexible tool suited for a variety of tasks normally performed by EVA's.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".