Automatic Animation Generation of a Teleoperated Robot Arm
Bibliographic record
Abstract
In this paper we describe the Automatic Task Demonstration Generator (ATDG), a system implemented into a software prototype for teaching the operation of a robot manipulator deployed on the International Space Station (ISS). The ATDG combines the use of path planning and camera planning to take into account the complexity of the manipulator, the limited direct view of the ISS exterior, and the unpredictability of lighting conditions in the workspace. The path-planning algorithm not only avoids obstacles in the workspace as is normal for a path-planner, but in addition takes into account the position of corridors for safe operations and the placement of cameras on the ISS. The camera planner is then invoked to find the right arrangement of cameras to follow the manipulator on its trajectory. This allows the on-the-fly production of useful and pedagogical task demonstrations to help the student carry out tasks involving the manipulation of the robot on the ISS. Even if the system has been developed for robotic manipulations, it could be used for any application involving the filming of unpredictable complex scenes.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".