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dc.contributor.authorNarasimhan, Mukund Venkatacharien_US
dc.date.accessioned2007-08-23T01:56:00Z
dc.date.available2007-08-23T01:56:00Z
dc.date.issued2007-08-23T01:56:00Z
dc.date.submittedDecember 2006en_US
dc.identifier.otherDISS-1550en_US
dc.identifier.urihttp://hdl.handle.net/10106/70
dc.description.abstractThe rising costs and demand coupled with shrinking energy generating resources has triggered the need for optimum use of energy resources, minimizing the overhead costs and maximizing the profits. Robots have been long touted as a fit replacement of human labor force in manufacturing sectors. Slowly there is increased presence of robots in automobile and electronic industries. Typically they are used for welding, painting, ironing, assembly, pick and place, inspection, and testing. Mass production, fulfilling the ever increasing demand, can be accomplished by robots because of their precision, speed of operation and high endurance capabilities. This dissertation comprises of two parts, the first part concentrates on optimizing the tool path. The path could be either a closed loop where in the robotic manipulator would get back to the home position after completing the task or could be an open segment where the manipulator would start and end at different locations after the completion of the task. Optimization of the tool path is similar to solving a Traveling Salesman Problem. A technique of insertion and reordering is applied to obtain an optimized tool path. The second part deals with the direct and inverse kinematics of the given robot configuration. A new notation, which takes into account all the six parameters necessary to define a rigid body in space, is developed to analyze kinematic analysis of industrial robots. Using the same notation, an inverse kinematics solver is used to compute the joint parameters necessary for the robot manipulator to reach the target point in space. This solver uses an iterative procedure to solve complex non-linear inverse kinematics problems. This solver tested on robots with revolute or prismatic or a combination of both yielded satisfactory results. The same solver can be used to analyze cylindrical, helical, spherical, combinations of all joints, planar and spatial mechanisms. The combination of optimizing the tool path and use of robots in the mass production of high demand products would go a long way in minimizing the costs, maximizing the profits and as well as delivering supply on time.en_US
dc.description.sponsorshipWang, Bo Pingen_US
dc.language.isoENen_US
dc.publisherMechanical Engineeringen_US
dc.titleOptimization Of The Tool Path In A Robotic Environmenten_US
dc.typePh.D.en_US
dc.contributor.committeeChairWang, Bo Pingen_US
dc.degree.departmentMechanical Engineeringen_US
dc.degree.disciplineMechanical Engineeringen_US
dc.degree.grantorUniversity of Texas at Arlingtonen_US
dc.degree.leveldoctoralen_US
dc.degree.namePh.D.en_US
dc.identifier.externalLinkhttps://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=275
dc.identifier.externalLinkDescriptionLink to Research Profiles


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