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Record W4321325504 · doi:10.2316/j.2023.201-0344

TRAJECTORY TRACKING OF NONHOLONOMIC CONSTRAINT MOBILE ROBOT BASED ON ADRC, 1-9. SI

2023· article· en· W4321325504 on OpenAlex
Cuiping Pu, Jie Ren, Youwen Zhai, Yuhang Zhang

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMechatronic systems and control · 2023
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsNonholonomic systemConstraint (computer-aided design)Tracking (education)Mobile robotTrajectoryControl theory (sociology)Computer scienceRobotArtificial intelligenceComputer visionControl engineeringMathematicsEngineeringControl (management)PhysicsPsychology

Abstract

fetched live from OpenAlex

The wheeled mobile robot is a typical uncertain robot system, which has typical nonholonomic characteristics and underdrive characteristics with different input and output dimensions.In the unknown environment, the slip and sideslip of the wheeled mobile robot are inevitable.Therefore, the research on trajectory tracking control of the wheeled mobile robot under sliding is of great significance.Aiming at the tracking problem of the wheeled mobile robot system with side slip disturbance, a Lyapunov design method based on extended state observer is proposed by using active disturbance rejection strategy.The influence of the sideslip disturbance on the system is regarded as the total disturbance of the system, and the extended state observer is used to observe the total disturbance in real time.The observation of the total disturbance by the extended state observer plays a patch role in the control law.When there is no disturbance, the system returns to the Lyapunov control under the nominal model.When there is a disturbance, the disturbance is compensated by the extended state observer, so that the system is approximately equivalent to the nominal model without being affected by the disturbance.The simulation results show that the system has better transient performance and anti-interference performance compared with the inverse control regardless of whether it is disturbed or not.

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)0.001
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 score0.959
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.233
Teacher spread0.218 · 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