Targeted Cognitive Training of Spatial Skills: Perspective Taking in Robot Teleoperation
Bibliographic record
Abstract
Spatial skills are critical for robot teleoperation. For example, in order to make a judgment of relative direction when operating a robot remotely, one must take different perspectives and make decisions based on available spatial information. Training spatial skills is thus critical for robot teleoperation, yet, current training programs focus primarily on psycho-motoric skills of the task, and less on the essential cognitive aspects of spatial skills. This work addresses this need by considering previous findings on relative direction judgments in training robot teleoperation. We developed and tested a basic training paradigm of perspective taking skill targeting the cognitive skill rather than psycho-motoric skill. An experiment tested a basic training paradigm using a stationary robot, with a training group receiving perspective taking training and a control group without training, and both tested on a transfer test with the robot. The results show that participants who went through a targeted cognitive skill training reached mastery level during the training, and performed better than the control group in an analogue transfer of learning test. Moreover, results reveal that the training facilitated participants with initial poor perspective taking skills reach the level of the high-skilled participants in transfer test performance. The study validates the possibility to target only cognitive aspects of spatial skills and result in better robot teleoperation.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".