Name
Abstract | ||
|---|---|---|
Cleaning is an important factor in most aspects of our day-to-day life. This research work brings a solution to the fundamental question of "How clean is clean" by introducing a novel framework for auditing the cleanliness of built infrastructure using mobile robots. The proposed system presents a strategy for assessing the quality of cleaning in a given area and a novel exploration strategy that facilitates the auditing in a given location by a mobile robot. An audit sensor that works by the "touch and inspect" analogy that assigns an audit score corresponds to its area of inspection has been developed. A vision-based dirt-probability-driven exploration is proposed to empower a mobile robot with an audit sensor on-board to perform auditing tasks effectively. The quality of cleaning is quantified using a dirt density map representing location-wise audit scores, dirt distribution pattern obtained by kernel density estimation, and cleaning benchmark score representing the extent of cleanliness. The framework is realized in an in-house developed audit robot to perform the cleaning audit in indoor and semi-outdoor environments. The proposed method is validated by experiment trials to estimate the cleanliness in five different locations using the developed audit sensor and dirt-probability-driven exploration. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.3390/s21134332 | SENSORS |
Keywords | DocType | Volume |
autonomous cleaning audit, cleaning benchmark, audit robot, dirt driven exploration | Journal | 21 |
Issue | ISSN | Citations |
13 | 1424-8220 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thejus Pathmakumar | 1 | 0 | 2.03 |
| Manivannan Kalimuthu | 2 | 0 | 0.34 |
| Rajesh Elara Mohan | 3 | 89 | 42.67 |
| Balakrishnan Ramalingam | 4 | 2 | 2.81 |