Abstract: Robotics in the construction industry has been used for a few decades up to this present time. There are various advanced robotics mechanisms or technologies developed for specific construction task to assist construction. However, not many researches have been found on the quality assessment of the finished structures. This research proposes a quality assessment robot that will assist in performing the assessment of the internal works of a building by assessing a quality assessment criterion in the Malaysian Construction Industry Standards. There are various assessment criteria such as hollowness, cracks and damages, finishing and jointing. This paper will focus on the wall evenness using a camera mounted on a mobile robot with a Mecanum wheel design. The wall evenness assessment was done via projecting a laser leveler on the wall and capturing the images by using a camera, which is later processed by a central controller. Results show that the deviation calculation method can be used to differentiate between even and uneven walls. Pixel deviations for even walls show values of less than 15 while uneven walls show values of more than 20 pixels.

Ahmad Zaki Shukor, Muhammad Herman bin Jamaluddin, Mohd Zulkifli bin Ramli, Ghazali bin Omar and Syed Hazni Abd Ghani, “Internal Works Quality Assessment for Wall Evenness using Vision-based Sensor on a Mecanum-Wheeled Mobile Robot” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130622

@article{Shukor2022,
title = {Internal Works Quality Assessment for Wall Evenness using Vision-based Sensor on a Mecanum-Wheeled Mobile Robot},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130622},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130622},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Ahmad Zaki Shukor and Muhammad Herman bin Jamaluddin and Mohd Zulkifli bin Ramli and Ghazali bin Omar and Syed Hazni Abd Ghani}
}