Cluster Synchronization of Predator Prey Robots
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
Bio-inspired robotics is an emerging field of cognitive intelligence which is based on the fundamental assumption that the biological systems are capable of self organization, better capable to adapt themselves to their changing environment for survival. Based on these features, behaviours observed in the biological world can be transferred to robots which may mimic the underlying behavior of their natural counterparts for efficient collaboration and coordination. The focus of this study is the application of identical unidirectionally coupled chaotic food webs in a robot foraging task. The phase coupled system is used to drive multi-robots arranged in a star network topology. The efficiency of the synchronization of the high dimensional system which is used to create a biologically inspired robot is examined using symbolic dynamics. In this work, the bio-inspired two wheeled mobile robots arranged in a topological network are assigned a set of targets or fixed obstacles distributed arbitrarily in the same workspace. The coverage is completed when a specified portion of the workspace is covered by the multi-robot system. Simulation results for coverage demonstrate the merit of the proposed system in the application of cooperative task assignment and obstacle avoidance.
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 | 0.001 |
| Open science | 0.001 | 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