Title :
Designing a mutating plan vector for a learning robot
Author_Institution :
Dept. of Comput. & Inf. Sci., Alabama A&M Univ., Normal, AL, USA
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;
Conference_Titel :
Southeastcon '89. Proceedings. Energy and Information Technologies in the Southeast., IEEE
Conference_Location :
Columbia, SC
DOI :
10.1109/SECON.1989.132371