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Record W2054660495 · doi:10.1109/rose.2014.6952979

Human arm motion imitation by a humanoid robot

2014· article· en· W2054660495 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
TopicRobot Manipulation and Learning
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsInterfacingHumanoid robotComputer scienceRobotic armUSableArtificial intelligenceComputer visionGestureRobotRobot controlMotion (physics)Motion controlHuman–robot interactionSoftwareMobile robotComputer hardware

Abstract

fetched live from OpenAlex

The objective of this work is the development of a system capable to control the arm movement of a robot by mimicking the gestures of an actor captured by a markerless vision sensor. The Kinect for Xbox is used to recuperate angle information at the level of the actor's arm and an interaction module transforms it into a usable format for real-time robot arm control. To avoid self-collisions, the distance between the two arms is computed in real-time and the motion is not executed if this distance becomes smaller the twice the diameter of the member. The interfacing issues are discussed and a software architecture is proposed and implemented for this purpose. The feasibility of our approach is demonstrated on a NAO robot.

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: none
Teacher disagreement score0.936
Threshold uncertainty score0.489

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 head0.015
GPT teacher head0.227
Teacher spread0.211 · 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

Citations28
Published2014
Admission routes1
Has abstractyes

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