The System for Wireless Communication in the Group of Cooperating Mobile Robots
Bibliographic record
Abstract
The Institute for Sustainable Technologies – NRI in Radom, together with Silesian University in Gliwice, have developed a group of mobile robots [1] intended for support of rescue actions. The group consists of two big robots: Explorer for exploring the environment and Transporter for transporting the number of small robots – Pathfinder (Fig. 1). The Explorer robot is capable of monitoring the environment in terms of temperature measurement, measuring the concentration of gases in the atmosphere and collecting the samples of soil. The Transporter is capable of transporting small robots and picking small objects as it is equipped with a container and a robotic arm and its purpose is to move small robots as close to the hazardous place as possible. Small robots called Pathfinder are intended to penetrate the area such as the room on fire and find potential victims or just allow the reconnaissance. All robots are equipped with one or more cameras and audio system for duplex communication. All the functions require the reliable and fast method of communication with enough bandwidth for the transmission of full duplex audio stream next to the simplex video stream and duplex control data stream.In the first part, the paper presents the brief overview of the market-available technologies for wireless communication; the second part presents the practical comparison test of selected products; and finally the last part of the paper describes the selected solution together with discussion on its capabilities.Fig. 1. Two of the group of four robots: small inspection robot and big transporter robotOne of the characteristic features of the designed group of robots is its low cost of production and maintenance, therefore the components used in the robot system could only be standard available constructions, but as the tests show, it is sufficient to fulfill the minimal requirement of range of at least fifty meters inside the typical building. Out of the considered communication equipment one of the commercially available Wi-Fi access point showed to be appropriate for the proposed application.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".