Continuously Varying Formation for Heterogeneous Multi-Agent Systems With Novel Potential Field Avoidance
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 article presents a novel approach to time-varying formation for heterogeneous multiagent systems (MASs), and uses a novel artificial potential field (APF) algorithm for collision and obstacle avoidance. For a team of agents, a set of formations are designed for the use case, and based on the circumstances for the system, the formation can be adjusted over a continuous spectrum of possible formations. This is done as a means of minimizing the amount of changing required in order for the formation to maneuver through an unknown environment. For obstacle avoidance, a modification to classical potential fields is implemented which utilizes the agent's heading, velocity, and other parameters to provide a better optimized avoidance algorithm. Terminal sliding mode controllers are applied for the control of the individual agents in the team. These are validated in both simulations and experiments for a team of quadrotor and mobile robots.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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