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Record W2025682449 · doi:10.1142/s0219843606000527

DESIGN, DYNAMIC MODIFICATION, AND ADAPTIVE CONTROL OF A NEW BIPED WALKING ROBOT

2006· article· en· W2025682449 on OpenAlexaff
Ahmad Bagheri, Farid Najafi, REZA FARROKHI, R. Yousefi Moghaddam, Mohammad Ebrahim Felezi

Bibliographic record

VenueInternational Journal of Humanoid Robotics · 2006
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsZero moment pointComputer scienceRobotControl theory (sociology)SwingMATLABSimulationRobot controlPoint (geometry)Control engineeringMobile robotControl (management)Artificial intelligenceHumanoid robotEngineeringMathematics

Abstract

fetched live from OpenAlex

Recently, a lot of research has been conducted in the area of biped walking robots that could be compared to human beings. The aim of this article is to control a new planar biped robot by means of an adaptive procedure. The newly designed robot is able to move on its heel like a human. After derivation of dynamic equations of motion for two states of the robot, namely, "supporting leg and trunk" and "swing leg" separately, the stability of robot is achieved by locating the zero moment point (ZMP). A dynamic modification is developed for ZMP positioning. For motion control of the robot, the physical parameters (such as mass, link length and geometry) are estimated (identified) by adaptive methods. A Matlab based software simulation is also conducted.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.014
GPT teacher head0.235
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2006
Admission routes1
Has abstractyes

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