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Bettaieb, Luc AlexandreA Deep Learning Approach To Coarse Robot Localization
Master of Sciences (Engineering), Case Western Reserve University, 2017, EECS - Electrical Engineering
This thesis explores the use of deep learning for robot localization with applications in re-localizing a mislocalized robot. Seed values for a localization algorithm are assigned based on the interpretation of images. A deep neural network was trained on images acquired in and associated with named regions. In application, the neural net was used to recognize a region based on camera input. By recognizing regions from the camera, the robot can be localized grossly, and subsequently refined with existing techniques. Explorations into different deep neural network topologies and solver types are discussed. A process for gathering training data, training the classifier, and deployment through a robot operating system (ROS) package is provided.

Committee:

Wyatt Newman (Advisor); Murat Cavusoglu (Committee Member); Gregory Lee (Committee Member)

Subjects:

Computer Science; Electrical Engineering; Robotics

Keywords:

robotics; localization; deep learning; neural networks; machine learning; state estimation; robots; robot; robot operating system; ROS; AMCL; monte carlo localization; particle filter; ConvNets; convolutional neural networks

Shah, ZubinSIMULATION AND ANALYSIS OF RFID LOCALIZATION ALGORITHMS
Master of Science in Computer Engineering (MSCE), Wright State University, 2006, Computer Engineering
Radio frequency identification (RFID) based localization systems provide a unique approach to localize mobile entities equipped with RFID readers or tagged with RFID tags. UHF RFID systems using passive tags are a good choice considering their cost, reading range, and reliability. With global acceptance and deployment of UHF RFID systems using passive tags for tracking and identification, virtually everything around us can be tagged with small and low-cost passive RFID tags. This thesis describes a Monte Carlo Localization based algorithm to localize a mobile RFID reader within a tagged environment. A software tool is developed to validate this localization process, simulate it and analyze its performance. Requirement specification for such RFID based localization systems can be determined based on various analysis plots available from this software tool. The tool also analyses tag localization using fixed readers to study the RFID characteristics for localization. These localization approaches can be used to provide intelligent context aware services.

Committee:

Jack Jean (Advisor)

Subjects:

Computer Science

Keywords:

RFID; Localization; Monte Carlo Localization; Simulation Tool; Real-time Localization

Kreinar, Edward JFilter-Based Slip Detection for a Complete-Coverage Robot
Master of Sciences (Engineering), Case Western Reserve University, 2013, EECS - Electrical Engineering
Complete-coverage robots, such as a lawnmower or snowplow, require a centimeter-level localization solution in order to navigate reliably. Unmodeled wheel slip or other odometry errors may cause localization to diverge beyond the bounds of uncertainty. Specifically in the case of a robot snowplow, errors due to wheel slip may be significant. This thesis uses the CWRU Cutter autonomous robot as a test platform to address the dual issues of (1) robust localization and (2) odometry error handling. Both an Extended Kalman Filter and an Adaptive Monte Carlo Localization procedure are derived and implemented specifically on the CWRU Cutter robot. Finally, a new augmented Extended Kalman Filter with general-purpose wheel-velocity error states is derived. The augmented EKF is shown to fully estimate the robot state and the wheel velocity error due to wheel slip during logged data from the 2013 Institute of Navigation's Autonomous Snowplow Competition.

Committee:

Roger Quinn, Dr. (Advisor); Francis Merat, Dr. (Committee Member); M. Cenk Cavusoglu, Dr. (Committee Member)

Subjects:

Computer Engineering; Electrical Engineering; Robotics

Keywords:

localization; odometry error; wheel slip; Extended Kalman Filter; Augmented Kalman Filter; Monte Carlo Localization; differential drive; robot lawnmower; robot snowplow