Using a robotic teleoperation system for haptic exploration
Bibliographic record
Abstract
INTRODUCTION: When children with physical impairments cannot perform hand movements for haptic exploration, they miss opportunities to learn about object properties. Robotics systems with haptic feedback may better enable object exploration. METHODS: Twenty-four adults and ten children without physical impairments, and one adult with physical impairments, explored tools to mix substances or transport different sized objects. All participants completed the tasks with both a robotic system and manual exploration. Exploratory procedures used to determine object properties were also observed. RESULTS: Adults and children accurately identified appropriate tools for each task using manual exploration, but they were less accurate using the robotic system. The adult with physical impairment identified appropriate tools for transport in both conditions, however had difficulty identifying tools used for mixing substances. A new exploratory procedure was observed, Tapping, when using the robotic system. CONCLUSIONS: Adults and children could make judgements on tool utility for tasks using both manual exploration and the robotic system, however they experienced limitations in the robotics system that require more study. The adult with disabilities required less assistance to explore tools when using the robotic system. The robotic system may be a feasible way for individuals with physical disabilities to perform haptic exploration.
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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 | 0.001 | 0.006 |
| 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) | 0.000 | 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".