MétaCan
Menu
Back to cohort
Record W2006728390 · doi:10.1115/detc2008-49453

Quasimoro: A Telerobot for the Augmentation of Wheelchair Users

2008· article· en· W2006728390 on OpenAlexafffund
Alessio Salerno

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsCanadian Space Agency
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesMcGill University
KeywordsTeleoperationTeleroboticsPayload (computing)RobotTask (project management)WheelchairComputer scienceHuman–computer interactionArchitectureGrippersMobile robotSimulationEngineeringArtificial intelligenceSystems engineering

Abstract

fetched live from OpenAlex

This paper focuses on the experiments conducted using a telerobot for the augmentation of wheelchair users. After providing the motivation and the background material, a strawman task is formulated. A robot is then conceived to meet the assigned task (i.e. user, environment and payload definitions). The proposed robot meets both cost and control simplification requirements necessary to the success of a robotic assistive device. A minimalistic design allows to achieve the requirements on cost and control complexity. An architecture based on a minimum number of driving units and sensors is devised. Experiments on the interactive control of the robot are performed. We demonstrate that the robot is capable to navigate through a cluttered environment while being teleoperated. Experiments also show that the system remains in its footpring when a rotation in place is assigned by the user; this is an important feature that prevents the system from colliding with any object nearby. Finally, always via experiments, we show that the system is capable to bring a tray of drinks, food and reading material while being teleoperated.

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.

How this classification was reachedexpand

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.121

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 head0.048
GPT teacher head0.269
Teacher spread0.221 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

Quick stats

Citations2
Published2008
Admission routes2
Has abstractyes

Explore more

Same topicGaze Tracking and Assistive TechnologyFrench-language works237,207