AN OPTIMAL PLANNING TECHNIQUE FOR AN INTELLIGENT ROBOTS PART ASSEMBLYIN PARTIALLY UNSTRUCTURED ENVIRONMENTS

An efficient algorithm for generating an optimal plan for part-bringin g tasks, using robotic manipulators, is introduced. The task of transp orting a micro-part in a partially unstructured environment, that incl udes obstacles whose locations are not initially known, is introduced with the optimal plan formulated on the basis of the observed environm ental conditions. Fuzzy set theory, well-suited to the management of u ncertainty, is introduced to address the uncertainty associated with t he part-bringing procedure. A part-bringing algorithm for generating t he optimal plan related to a part assembly, despite existing obstacles , is presented. It is shown that the machine organizer using a sensor system can intelligently determine an optimal plan, based on explicit performance criteria, to overcome environmental uncertainty. The algor ithm utilizes knowledge processing functions such as machine reasoning , planning, memory, and decision-making. Simulation results show the e ffectiveness of the proposed approach. The proposed algorithm is appli cable not only to a wide range of robotic tasks including pick and pla ce operations and maneuvering mobile based robots around obstacles, bu t also to the control of unmanned aircraft.