SENORA: A P2P Service-Oriented Framework for Collaborative Multirobot Sensor Networks
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
SENORA is an open hardware and software architecture for the cooperative coordination of multiple heterogeneous mobile robots operating in a common environment. It is designed to meet the stringent requirements of modern loosely coupled multirobot architectures, such as flexibility, reliability, and fault tolerance. As such, the proposed architecture enables the robots to cope with the ubiquitous presence of various types of uncertainties in their operating environments. SENORA is a fully autonomous and scalable sensory-based peer-to-peer (P2P) framework. It also offers a real-time inter-robot communication protocol and it is based on the state-of-the-art P2P technology, which is specifically designed to satisfy the requirements of physical sensory data publishing and fusion. This architecture is implemented and evaluated on a team of indoor mobile robots. The test results manifest the architecture's distinguished features and capabilities
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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