Evaluation of Smartphone-based Interfaces for Navigation Tasks in Unstructured Environments for Ground Robots
Why this work is in the frame
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Bibliographic record
Abstract
The development of robots that autonomously assist humans is still a challenge in unstructured domestic environments. A practical approach is through teleoperation. Conventional teleoperation uses specialized mechanical devices that provide user-friendly interfaces to operate robots, but these devices might be complex and expensive. In this paper, we compare the performance of three smartphone-based interfaces for robot navigation tasks. First, we show our system setup and our simulated domestic environments, then, we present our three smartphone-based interfaces that leverage the capabilities of ubiquitous smartphones to allow users to operate a domestic robot -PR2- in the simulated environments. Subsequently, we explain the procedure to complete our usability study. In this study, we establish completion time and the path smoothness as objective measurements, and we combine these measurements with a Nasa-TLX evaluation. Finally, we show our usability study results, and we present our conclusions.
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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 it