A new robot can inspect a building for defects faster and more accurately than humans, saving time and manpower with  laser scanners and cameras. Meet QuicaBot, which has a special talent in finding fault. This new robot, invented by a group of four scientists from Nanyang Technological University (NTU). The high technology camera used in the robot to help detect defects and uneven surfaces faster and more thoroughly than humans. Usually, human inspectors use tools such as set squares and spirit levels to check whether walls meet at right angles and floors are even. Accompanied by a human inspector, it can finish checking a 200 sq m room in 20 minutes, compared to the 45 minutes two building inspectors may spend to do the same. Research into the QuicaBot (Quality Inspection and Assessment Robot) which is  co-developed by national industrial developer JTC and a Singapore start-up, CtrlWorks which is backed by the National Research Foundation.

If that field trial proves successful, the team could then look at how to scale up for potential commercial applications. QuicaBot can move autonomously and use a combination of five different scanners and cameras to inspect for evenness, squareness which are set at a 90-degree angle, and cracks in the walls, ceilings and floors. Standard manual inspection using human effort rely on tools such as set squares and metal rods. While human inspectors may make sampling errors due to the limited number of checks they can do and the fatigue experienced, the QuicaBot will be able to check a room more comprehensively and accurately. After scanning, the robot can produce a 3D map of the space with the defects highlighted, and the information can be uploaded online for access by building owners and inspectors, who can then inspect critical and complex defects.

At its present R&D phase, there is still potential for the QuicaBot to be fully automated and improved with enhanced reliability and efficiency in the inspection of buildings,” its spokesperson said. Development of the robot started in July 2015 and will end next January, with the team now working on fine-tuning the algorithm for the cameras and inclinometer. In the first quarter of 2017, it will be deployed for test-bedding at JTC Space @ Gul in Tuas, a facility being developed for manufacturing companies.