Range based target capture and station keeping of nonholonomic vehicles without GPS
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.
Bibliographic record
Abstract
This paper studies the closely related problems of target capturing and station keeping by an autonomous vehicle agent within the limitations of having access to the measurements of distance from the target only, where station keeping refers to moving the agent to a position having predefined distances from a network of sensory stations or other agents. These problems have been recently studied for the cases where the position of the agent is available for measurement. The objective of this paper is to design a control scheme for solving the same problems when the self-position measurement is not available. In practical UAV settings, this corresponds to consideration of unavailability of GPS. Following the approach of another recent work for circumnavigation problems with the same measurement setting, a control scheme is proposed for each of the two aforementioned problems using agent-target range and range rate information. The paper provides a brief analysis of stability and convergence properties and some simulation results demonstrating performance of the proposed control schemes.
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 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 | 0.000 |
| 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 it