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dc.contributor.advisorPopa, Dan
dc.creatorTorres, Nahum Arenas
dc.date.accessioned2017-09-13T14:27:24Z
dc.date.available2017-09-13T14:27:24Z
dc.date.created2016-05
dc.date.issued2016-05-16
dc.date.submittedMay 2016
dc.identifier.urihttp://hdl.handle.net/10106/26919
dc.description.abstractThe field of untethered microrobotics has emerged within the last two decades for its applications potential in military surveillance, micro and nano manufacturing, as well as in health care for minimal invasive surgery and drug delivery. Microrobots need to be fast and precise in order to be useful as a tool for manufacturing applications. It is well understood that at this size scale numerous challenges prevail such as stiction between microrobot and environment, providing power, locomotion control, and intelligence to microrobots and motion measurement. In order to accelerate the research in this field, I participated in the Mobile Microrobotics Challenge (MMC). MMC is an annual event organized by the Institute of Electrical and Electronics Engineers Robotics and Automation Society (IEEE RAS) since 2013 and designed to encourage researchers around the world to solve pressing challenges in microrobotics. The challenge is composed of three events: 1) the autonomous mobility and accuracy challenge, 2) the microassembly challenge and 3) the MMC showcase and poster session. These challenges simulate common tasks that are found in medical applications, involving high speed closed-loop positioning, and in microassembly applications involving precision motion control and the later and the showcase and poster challenge tests your communication skills. This thesis investigates and provides methods to mitigate the problems of stiction, locomotion control, and motion measurement for microrobots. In addition, we discuss novel methods for providing cooperative behavior to multiple microrobots and to estimate and mitigate spatial uncertainty estimation for modular serial link robotic platforms. In this dissertation I describe novel methods to enhance the performance of magnetic microrobots, reduce environmental forces via inexpensive anti-friction coatings, and increase their velocities via novel mechanical amplifiers. Such methods generate swarming motions, with a leader and formation following behavior, and cooperative planar motions compatible with micromanipulation tasks such as grasping. Moreover, I provide a possible application scenario using such cooperative behavior to assemble optical elements. The cooperative grasping behavior is produced by the magnetic field gradient controlled by a modular multi-degree of freedom serial link robot used to position the conical permanent magnet with respect to the robots’ workspace. In the course of this research it was necessary to precisely characterize and compensate for the spatial uncertainty of the robot. Spatial uncertainty is an inherent feature of multiple-link robots due to misalignment of joints, link length, resolution of the actuator, the type of joint, the path of motion and the atmosphere of operation. Such uncertainties can be detrimental for robots used in assembly tasks where precision is essential. In order to overcome this fundamental challenge with flexible or modular assembly and packaging systems, I presents a novel precision evaluation and control technique to estimate and track the end-effector position errors in a robotic manipulation system resulting from the kinematic configuration as well as the dynamic parameters for each specific task; thereby, allowing the automation application to compensate for these errors in run-time.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectUntethered microrobots
dc.subjectCooperative micromanipulation
dc.subjectMagnetic microrobots
dc.subjectMicrorobots
dc.titleCOOPERATIVE CONTROL OF MULTIPLE UNTETHERED MAGNETIC MICROROBOTS FOR PRECISION MICROMANIPULATION
dc.typeThesis
dc.degree.departmentElectrical Engineering
dc.degree.nameDoctor of Philosophy in Electrical Engineering
dc.date.updated2017-09-13T14:27:24Z
thesis.degree.departmentElectrical Engineering
thesis.degree.grantorThe University of Texas at Arlington
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy in Electrical Engineering
dc.type.materialtext
dc.creator.orcid0000-0002-0023-3440


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