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Record W1590063992 · doi:10.1109/iscas.2006.1693144

A cooperative network of reconfigurable stair-climbing robots

2006· article· en· W1590063992 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
TopicModular Robots and Swarm Intelligence
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTraverseRobotClimbStair climbingStairsModular designComputer scienceControl reconfigurationMobile robotClimbingRobot controlObstacleEmbedded systemControl engineeringDistributed computingSimulationEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The work area of a team of small robots is limited by their inability to traverse a very common obstacle: stairs. We present a complete integrated control architecture and communication strategy for a system of reconfigurable robots that can climb stairs. A modular robot design is presented which allows the robots to dynamically reconfigure to traverse certain obstacles. This work investigates the implementation of a system of autonomous robots which can cooperatively reconfigure themselves to collectively traverse obstacles such as stairs. We present a complete behavior and communication system which facilitates this autonomous reconfiguration. The behavior and communication systems are validated by implementing them on a mobile robot platform synthesized specifically for this research. Experimental trials showed that the implementation of the behavior control systems was successful. Several successful stair climbing trials were accomplished. Improvements to the mechanical design are proposed

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 score0.921
Threshold uncertainty score0.776

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)0.0010.000

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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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

Citations10
Published2006
Admission routes1
Has abstractyes

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