VIRTUAL REALITY MODELING, ANALYSIS AND SIMULATION OF FORMATION FLYING OF TWO UNMANNED AERIAL VEHICLES
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
The objective of this paper is to show a complete simulation and implementation of multiple unmanned aerial vehicles (UAV), with emphasis on the requirements needed and the benefits realized in making the simulation functional for an arbitrary number of vehicles. Cooperative control is shown for an autonomous set of vehicles in performance of tasks such as formation, reconnaissance, surveillance, search, jamming and decoy or target attack. The simulation is developed using a Commercial off the Shelf (COTS) software package that allows for a hierarchical block diagram representation to include control laws and vehicle models. Visualization is achieved by having the simulation drive a VRML (Virtual Reality Modeling Language) world allowing the interactions of the vehicles in their environment to be seen as the simulation is running. Implementation is done using Micropilot an auto pilot system developed by Canadian based company, which can be interfaced with Horizon. The HORIZON ground control software is a user-friendly interface for Communicating with your MicroPilot Autopilot. The control law is implemented with position estimation.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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 it