Optimal planning technique with a fuzzy co-ordinator for an intelligent robot´s part assembly

An optimal planning technique with a fuzzy co-ordinator for intelligent robot assembly is introduced. A fuzzy intelligent organising control strategy, based on a fuzzy rule-base and derived from measured force/moment data, for a robotic device performing quasistatic assembly tasks is presented. Fuzzy set theory, which is well suited to manage the uncertainty problem, is introduced to deal with the uncertainty associated with a part assembly. Fuzzy entropy is employed to measure the uncertainty (fuzziness) as it is related to specific control actions. The top organising level determines the most appropriate sequence of events of a plan with minimum fuzziness by utilising the knowledge processing functions, such as machine memory, inferencing, planning, and decision-making, and downlinks it to the lower level of the system that carries out the specified task. Experimental results show the effectiveness of the proposed approach