• DocumentCode
    276893
  • Title

    Artificial intelligence and robotic construction plant-the `smart artisan´

  • Author

    Bradley, D.A. ; Seward, D.W.

  • Author_Institution
    Dept. of Eng., Lancaster Univ., UK
  • fYear
    1992
  • fDate
    33619
  • Firstpage
    42583
  • Lastpage
    42586
  • Abstract
    Robots and automated systems are now well established in the manufacturing industry where the operating environment can in general be modified and adapted to their requirements. As yet, however, these same technologies have had little impact in the unstructured, hostile and highly variable environment of a construction site. In order to function and survive in a site environment, construction robots will have to be highly adaptive, responding rapidly to changes in their operating conditions by making a series of strategic and tactical decisions about their mode of operation. This may be illustrated by considering the requirements for an automated and robotic excavator. The development of a hierarchical, Al based control system for robotic excavation has been the objective of the Lancaster Construction Robotics Group. Referred to as the `smart artisan´ because of its function and application this system has been implemented as the Lancaster University Computerised Intelligent Excavator (LUCIE) project on a JCB801 tracked excavator and has proved capable of autonomously digging a trench to a controlled depth in a variety of ground types and conditions and of overcoming and removing obstacles such as boulders without operator intervention
  • Keywords
    adaptive systems; construction industry; knowledge based systems; mobile robots; LUCIE project; Lancaster University Computerised Intelligent Excavator; adaptive systems; artificial intelligence; construction site; control system; manufacturing industry; robotic construction plant; robotic excavator;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Artificial Intelligence in Civil Engineering, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • Filename
    167665