Formation control of a team of single-integrator agents with measurement error
Bibliographic record
Abstract
This paper investigates the formation control problem for a team of single-integrator agents subject to distance measurement error. Collision, obstacle and boundary avoidance are important features of the proposed strategy. It is assumed that upper bounds exist on the magnitude of the measurement error and its derivative w.r.t. the measured distance. A decentralized navigation function is then proposed to move the agents toward a desired final configuration which is defined based on the pairwise distances of the connected agents and the characteristics of the distance measurement error. Conditions on the magnitude of the measurement error and its derivative w.r.t. the measured distance are derived under which a new formation configuration can be achieved anywhere in the space due to the measurement error. This error-dependent formation can be determined exactly if the error model is available. If such a model is not available, the maximum discrepancy in the final distances can be obtained in terms of the maximum measurement error. Moreover, the control law designed based on the navigation function ensures collision, obstacle and boundary avoidance in the workspace. The efficacy of the proposed control strategy is demonstrated by simulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".