AndroRC: An Android remote control car unit for search missions
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 AndroRC is a remote control car (RC) unit controlled by a smartphone running on an Android application. The car is meant to be used in search missions in the occurrence of natural disasters. It is developed to autonomously avoid obstacles that are not visible to the user driver. The RC unit is developed based on a Tamiya 70112 Buggy car chassis set with an extra servo motor added to provide the left and right directions. The RC is equipped with an ultrasonic distance sensor, a camera, a Bluetooth receiver, a Wi-Fi transmitter, two 9-V batteries and two Arduino microcontroller boards (UNO and MEGA). The Arduino MEGA controls the propulsion and direction, while the UNO processes the information received from the distance sensor to stop the RC at a pre-defined distance. The Android application uses the embedded orientation sensor on the smartphone to determine the four directions (forward, backward, left and right) intended by the user; hence, rotating the smartphone to different directions results in to the corresponding propulsion of the RC unit. The control commands are transmitted to the RC unit through the Bluetooth communication. The Android application also receives (via Wi-Fi) and displays the information from the camera in real-time. The AndroRC was characterized and examined on bench-top settings.
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 | 0.000 |
| 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