A neural network approach to the redundant robot inverse kinematic problem in the presence of obstacles

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dc.contributor.advisorCheatham, John B., Jr.en_US
dc.creatorNorwood, John Daviden_US
dc.date.accessioned2009-06-04T00:16:45Zen_US
dc.date.available2009-06-04T00:16:45Zen_US
dc.date.issued1991en_US
dc.description.abstractRedundancy in robots is very much an open research area in the field of robotics. As the tasks required of robots become more and more complex, the ability of robots to perform satisfactorily in these applications must increase accordingly. Redundant manipulators have a greater ability to perform difficult tasks, such as obstacle avoidance, than non-redundant ones. In order to make use of this extra ability of redundant robots, more effective control schemes must continue to be developed and to this end, more and more researchers are looking to expand the body of knowledge in this area. This thesis addresses the problem of moving a redundant robot within a defined workspace in the presence of obstacles. Additionally, criteria are developed that may be applied to the robot to constrain the redundant equations. Finally, a neural network solution to the redundant inverse kinematic problem is presented. It will be shown that the inverse kinematics can be developed through a network architecture which provides accurate and fast solutions to a problem that is computationally and structurally complex. This effort will be kept within the context of already accepted methods currently in use for redundant robots, the overall goal of this research being to firmly establish the usefulness and applicability of neural network architectures to difficult robotic problems.en_US
dc.format.extent167 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoThesis M.E. 1991 Norwooden_US
dc.identifier.citationNorwood, John David. "A neural network approach to the redundant robot inverse kinematic problem in the presence of obstacles." (1991) Diss., Rice University. <a href="https://hdl.handle.net/1911/16468">https://hdl.handle.net/1911/16468</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/16468en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectMechanical engineeringen_US
dc.subjectNeurosciencesen_US
dc.subjectElectronicsen_US
dc.subjectElectrical engineeringen_US
dc.subjectBiologyen_US
dc.subjectEngineeringen_US
dc.titleA neural network approach to the redundant robot inverse kinematic problem in the presence of obstaclesen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentMechanical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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