• DocumentCode
    3312378
  • Title

    Designing a mutating plan vector for a learning robot

  • Author

    Das, Asesh

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Alabama A&M Univ., Normal, AL, USA
  • fYear
    1989
  • fDate
    9-12 Apr 1989
  • Firstpage
    262
  • Abstract
    Mutating plan vector design for a learning robot is discussed with emphasis on the need for a Skolemized knowledge base. In the proposed model, a plan is defined as a vector between the start frame and the goal frame. This vector is composed of partially ordered bases consisting of task-level and robot level parameters. When the robot fails to work according to a given plan, mutations of some of the bases are said to have taken place. For further mutations in a correct direction, the robot needs knowledge base support. The knowledge base is Skolemized and a unification mechanism operates
  • Keywords
    learning systems; robots; Skolemized knowledge base; learning robot; learning systems; mutating plan vector; robot level parameters; task-level; unification mechanism; Genetic mutations; Intelligent robots; Intelligent sensors; Kinetic theory; Monitoring; Motion planning; Orbital robotics; Process planning; Robot sensing systems; Robotics and automation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Southeastcon '89. Proceedings. Energy and Information Technologies in the Southeast., IEEE
  • Conference_Location
    Columbia, SC
  • Type

    conf

  • DOI
    10.1109/SECON.1989.132371
  • Filename
    132371