Design and Implementation Low Cost Smart Cleaner Mobile Robot in Complex Environment
Bibliographic record
Abstract
The mobile robot is widely used in many cleaning applications.This paper presents the design and implementation of a low-cost smart cleaner wheeled mobile robot for floor cleaning applications.The robot is capable of accurately navigating through various environments and avoiding obstacles.The paper focuses on three main points: interfacing the motion modeling equations with an Android application, designing a differential mobile robot with flexible mobility, and incorporating obstacle avoidance using an Ultrasonic sensor.The results demonstrate that the robot can move with high precision and flexibility, with minimal error.The maximum error on the complex (carpet) floor equals (±1.1500 cm) and it is greater than the maximum error on the flat floor which equals (±0.5800 cm).Additionally, the robot's affordability, priced at 28 $.The designed mobile robot is low cost, for this reason it accessible to anyone seeking a cleaning solution for both flat and rough (complex) floors, whether dry or wet.From these specifications of designed mobile robot, it considered better than related works.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".