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State Estimation of an Acoustic Bubble-Powered Microswimmer from Ultrasound Imaging Data

Xiao, Zunding (2019) State Estimation of an Acoustic Bubble-Powered Microswimmer from Ultrasound Imaging Data. Master's Thesis, University of Pittsburgh. (Unpublished)

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Tiny and untethered robots can navigate into narrow blood arteries and in vivo tissues. Such a revolutionary device brings the possibility of delivering drugs to a specific target and medical diagnosis of diseases that may not be feasible with conventional treatment and diagnosis. Current medical micro-robot technology uses externally-generated magnetic fields. The actuation technology, although external to the micro-robot, is expensive and bulky. There is also always a risk of damaging human tissues with this technique. A promising recent technology uses acoustic waves as a power source for a micro swimming robot. An acoustic power source is extremely small compared to a magnetic field power source and there is a very little risk of any damage to the tissues during the micro-robot actuation. This thesis presents dynamic modeling and state estimation of a novel underwater swimming micro-robot that is powered through oscillations of gas bubbles trapped inside the micro-robot.
The rectangular shaped, which is made of photoresist, has the dimensions of 950 μm × 460 µm × 340 μm. The motion is produced by the oscillations of gaseous bubbles trapped in the micro-tubes. Primarily acoustic waves induce oscillations at a certain frequency and thus are used as a propulsion mechanism to realize 3 degree-of-freedom swimming motion. Ultrasound imaging is proposed to sense the swimming motion of the micro-robot.
The main focus of the thesis is on the development of an estimator that detects swimming motion of the micro-robot from ultrasound imaging data. A new class of nonlinear state estimation method, called state-dependent coefficient (SDC) estimator, is implemented to improve the accuracy of micro-robot state estimation. The estimator is also used to predict rotation of the robot, which cannot be measured by ultrasound imaging due to the robot’s extremely small size. Experiments and simulations were carried out to verify the accuracy of the estimator and the performance of the estimator coupled with a closed-loop controller.
A dynamic model that captures the acoustic actuation was also developed. The model is used in the SDC estimator and was also used to develop a nonlinear control law that tracks a desired swimming motion. The model includes a switching mechanism that was designed to produce bidirectional swimming motion (e.g., left turn and right turn). Each channel that holds the gas bubbles can produce only unidirectional movement. The mechanism switches between counteracting tubes to produce bidirectional movement. The input switch mechanism was demonstrated in a simulation study of the micro-swimmer.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Xiao, Zundingzux2@pitt.eduzux2
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorSharma, Nitinnis62@pitt.eduNIS62
Committee MemberCho, Sung
Committee MemberKim,
Date: 23 January 2019
Date Type: Publication
Defense Date: 24 July 2018
Approval Date: 23 January 2019
Submission Date: 17 July 2018
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 59
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Mechanical Engineering
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: micro-swimmer, state dependent coefficient estimation, ultrasound image tracking
Date Deposited: 23 Jan 2019 16:29
Last Modified: 19 Jul 2024 19:41


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