Akrawi, S G (1998) Sensing and real-time expert system for a masonry building robot. PhD thesis, City, University of London, UK.
Abstract
The construction industry is striving to eliminate dangerous and repetitive work, as well as increase quality and productivity in the various tasks. For this reason, there is growing interest in the use of automation and robotics. However, the requirements of robots for construction are different from those of industrial robots, due to the characteristics of the construction tasks and the relatively unstructured working environment. The main objective of this research is to investigate the enabling technology for a masonry tasking robot, utilising an experimental robot cell. To truly automate the masonry construction tasks, there is need to utilise the advancement in robotic technology, especially to deal with the unstructured environment. This view is in-line with this research, which attempts to solve part of the complex problems of automating the building task, by using forms of sensing and intelligence. Concentration on this is the main distinguishing difference between this work and the few other attempts at physical realisation and experimentation in masonry automation. In terms of research and development of masonry tasking machines and robots, there is much activity on an international scale. Concerning the provisions for machine intelligence in this, it appears that the work reported has the most advanced provisions for computer intelligence. This work is of general relevance to construction robots because imprecision, dynamic performance, unplanned events and cell component relocation are considered. The experimental robot cell, built at City University, is used in the research. Standard construction materials have been adopted with imprecise dimensions. Using a CAD/CAM facility, building project designs are translated into robot's 'theoretical task'. However, because the masonry material is unpredictable, this can not be directly implemented without real-time adjustments derived from sensing. Notwithstanding, advantage is taken of pre-processing, with real-time accommodation of discrepancies, obstacle avoidance and un-planned events.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | automation; expert system; masonry; productivity; robotic |
| Index terms: | productivity, project design, dimension, automation, construction industry, robotics, construction material, relocation, experiment, expert system, research and development |
| Subjects: | research management, market analysis, automation and robotics, contractual arrangements, industry analysis, data management, management, health monitoring assessment and metrics, building materials, data collection methods |
| Topics: | Procurement, Engineering Principles, Health and Safety, Digital Applications, Research Practice, Business Strategy |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here