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Record W2908092972 · doi:10.1109/ccra.2018.8588148

Evaluation of Smartphone-based Interfaces for Navigation Tasks in Unstructured Environments for Ground Robots

2018· article· en· W2908092972 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotics and Automated Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTeleoperationUsabilityLeverage (statistics)Human–computer interactionComputer scienceRobotMobile robotInterface (matter)Embedded systemSimulationArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.281
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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