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          <dc:identifier>https://hdl.handle.net/2286/R.I.40236</dc:identifier>
                  <dc:rights>http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
          <dc:rights>All Rights Reserved</dc:rights>
                  <dc:date>2016</dc:date>
                  <dc:format>xiv, 209 pages : illustrations (some color)</dc:format>
                  <dc:type>Masters Thesis</dc:type>
          <dc:type>Academic theses</dc:type>
                  <dc:language>eng</dc:language>
                  <dc:contributor>Lu, Xianglong</dc:contributor>
          <dc:contributor>Rodriguez, Armando Antonio</dc:contributor>
          <dc:contributor>Berman, Spring</dc:contributor>
          <dc:contributor>Artemiadis, Panagiotis</dc:contributor>
          <dc:contributor>Arizona State University</dc:contributor>
                  <dc:description>Partial requirement for: M.S., Arizona State University, 2016</dc:description>
          <dc:description>Includes bibliographical references (pages 145-146)</dc:description>
          <dc:description>Field of study: Electrical engineering</dc:description>
          <dc:description>To achieve the ambitious long-term goal of a feet of cooperating Flexible Autonomous&lt;br/&gt;&lt;br/&gt;Machines operating in an uncertain Environment (FAME), this thesis addresses several&lt;br/&gt;&lt;br/&gt;critical modeling, design, control objectives for rear-wheel drive ground vehicles.&lt;br/&gt;&lt;br/&gt;Toward this ambitious goal, several critical objectives are addressed. One central objective of the thesis was to show how to build low-cost multi-capability robot platform&lt;br/&gt;&lt;br/&gt;that can be used for conducting FAME research.&lt;br/&gt;&lt;br/&gt;A TFC-KIT car chassis was augmented to provide a suite of substantive capabilities.&lt;br/&gt;&lt;br/&gt;The augmented vehicle (FreeSLAM Robot) costs less than $500 but offers the capability&lt;br/&gt;&lt;br/&gt;of commercially available vehicles costing over $2000.&lt;br/&gt;&lt;br/&gt;All demonstrations presented involve rear-wheel drive FreeSLAM robot. The following&lt;br/&gt;&lt;br/&gt;summarizes the key hardware demonstrations presented and analyzed: &lt;br/&gt;&lt;br/&gt;(1)Cruise (v, ) control along a line, &lt;br/&gt;&lt;br/&gt;(2) Cruise (v, ) control along a curve,&lt;br/&gt;&lt;br/&gt;(3) Planar (x, y) Cartesian Stabilization for rear wheel drive vehicle, &lt;br/&gt;&lt;br/&gt;(4) Finish the track with camera pan tilt structure in minimum time, &lt;br/&gt;&lt;br/&gt;(5) Finish the track without camera pan tilt structure in minimum time, &lt;br/&gt;&lt;br/&gt;(6) Vision based tracking performance with different cruise speed vx, &lt;br/&gt;&lt;br/&gt;(7) Vision based tracking performance with different camera fixed look-ahead distance L, &lt;br/&gt;&lt;br/&gt;(8) Vision based tracking performance with different delay Td from vision subsystem, &lt;br/&gt;&lt;br/&gt;(9) Manually remote controlled robot to perform indoor SLAM,&lt;br/&gt;&lt;br/&gt;(10) Autonomously line guided robot to perform indoor SLAM.&lt;br/&gt;&lt;br/&gt;For most cases, hardware data is compared with, and corroborated by, model based&lt;br/&gt;&lt;br/&gt;simulation data. In short, the thesis uses low-cost self-designed rear-wheel&lt;br/&gt;&lt;br/&gt;drive robot to demonstrate many capabilities that are critical in order to reach the&lt;br/&gt;&lt;br/&gt;longer-term FAME goal.</dc:description>
                  <dc:subject>Electrical Engineering</dc:subject>
          <dc:subject>Computer Science</dc:subject>
          <dc:subject>Robotics</dc:subject>
          <dc:subject>Control Theory</dc:subject>
          <dc:subject>SLAM</dc:subject>
          <dc:subject>Mobile robots</dc:subject>
          <dc:subject>Vehicles, Remotely piloted--Design and construction.</dc:subject>
          <dc:subject>Vehicles, Remotely piloted</dc:subject>
          <dc:subject>Vehicles, Remotely piloted--Automatic control.</dc:subject>
          <dc:subject>Vehicles, Remotely piloted</dc:subject>
                  <dc:title>Modeling and control for vision based rear wheel drive robot and solving indoor SLAM problem using LIDAR</dc:title></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>
