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Record W3012284353 · doi:10.1109/cdc40024.2019.9029296

Optimal Distance-Based Formation Producing Control of Multi-Agent Systems with Energy Constraints and Collision Avoidance

2019· article· en· W3012284353 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
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsCollision avoidanceCollisionComputer scienceControl (management)Energy (signal processing)Control theory (sociology)Multi-agent systemMathematicsComputer securityArtificial intelligence

Abstract

fetched live from OpenAlex

This paper considers the problem of an optimal distance-based formation producing control for multi-agent systems. We use the rigid graph theory in combination with the state-dependent Riccati equation (SDRE) method to develop a multi-agent formation producing scheme. We define a normalized rigidity matrix and use it for the rigorous stability analysis. A quadratic-like cost functional is defined that takes into account the cost of the formation as well as the energy cost. The proposed control law asymptotically minimizes the cost functional while it assures local asymptotic stability of the closed-loop system. Furthermore, we propose a solution for the global asymptotic stability and collision avoidance. In order to verify and validate theoretical results, we present several simulation results in both 2-D and 3-D spaces.

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 score0.934
Threshold uncertainty score0.677

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 communication0.0000.001
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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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