Mobile robotic active view planning for physiotherapy and physical exercise guidance
Bibliographic record
Abstract
Consulting a physiotherapist or physical trainer for long term regular exercises is not financially affordable for all. As a solution, our long term research goal is to develop a robotic physiotherapist/physical trainer which could instructively and physically guide a performer. Towards that direction, in this paper we present an autonomously repositioning mobile robot to observe a person throughout a sequence of physical exercises by selecting less self-occluded viewpoints. A viewpoint specific joint mutual occlusion (JMO) measurement is formulated at candidate viewpoints. Then a utility function, which accounts for joint occlusion, skeleton coverage, sensing range and moving cost, is averaged over the sub-activity periodic duration to find the optimal viewpoint. Proposed methods have been evaluated with multi-view dataset and an online mobile robot while a person performed eight different physical activities with two trials each. Results indicate proposed active view planner can autonomously drive the mobile robot to a less self-occluded viewpoint over manually setup fixed viewpoint observation, leading to more accurate human movement analysis.
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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 | 0.000 |
| 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 | 0.000 | 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".