A fuzzy expert organizer/robust control strategy for a moving base robotic part assembly

In this paper, three analytical tasks, stability analysis, robust control, and fuzzy intelligent organizer for a moving base robot are introduced. These tools are necessary for a mobile robot to perform complex assembly or manufacturing tasks in an unstructured environment. A stability envelope based on the relations between the system´s mechanical energy and the stability relation is derived. A robust control algorithm is applied to the moving base robot that accounts for the dynamics of the composite system. A fuzzy intelligent organizing control strategy, based on a fuzzy rulebase and derived from measured force/moment data, for a robotic device performing quasi-static assembly tasks is presented. A modified distance metric is employed to measure the uncertainty (fuzziness) as it is related to specific control actions. A learning algorithm based on the probability of a fuzzy event is introduced. The top organizing level determines the most appropriate n-tuple control values with minimum fuzziness and downlinks them to the lower level of the system which carries out the specified task. Experimental results show the effectiveness of the proposed approach. Finally a hierarchical controller which consists of a higher level fuzzy expert organizer coordinating with a lower level robust controller is proposed. Experimental and simulation results are used to demonstrate the effectiveness of the algorithms