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Record W1997462935 · doi:10.1142/s0219843614500145

Bibot-U6: A Novel 6-DoF Biped Active Walking Robot - Modeling, Planning and Control

2014· article· en· W1997462935 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

VenueInternational Journal of Humanoid Robotics · 2014
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceRobotKinematicsRobustness (evolution)Biped robotControl theory (sociology)AdaptabilityDegrees of freedom (physics and chemistry)SimulationControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

Most of current biped robots are active walking platforms. Though they have strong locomotion ability and good adaptability to environments, they have a lot of degrees of freedom (DoFs) and hence result in complex control and high energy consumption. On the other hand, passive or semi-passive walking robots require less DoFs and energy, but their walking capability and robustness are poor. To overcome these shortcomings, we have developed a novel active biped walking robot with only six DoFs. The robot is built with six 1-DoF joint modules and two wheels as the feet. It achieves locomotion in special gaits different from those of traditional biped robots. In this paper, this novel biped robot is introduced, four walking gaits are proposed, the criterion of stable walking is addressed and analyzed, and walking patterns and motion planning are presented. Experiments are carried out to verify the locomotion function, the effectiveness of the presented gaits and to illustrate the features of this novel biped robot. It has been shown that biped active walking may be achieved with only a few DoFs and simple kinematic configuration.

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 score0.962
Threshold uncertainty score0.742

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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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