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Design and control of DermDrone; a micro-sized quadrotor for dermatology applications with RL-based optimization

Resource type
Thesis type
(Thesis) M.A.Sc.
Date created
2021-12-14
Authors/Contributors
Abstract
Melanoma is the most serious type of skin cancer in the world, and its prevalence has increased in recent years. Total Body Photography (TBP) is a well-known tool for early diagnosis of melanoma, which significantly improves the chance of its treatment's success. Current commercial TBP systems present several challenges, including their expense, bulkiness, and requirement for a large, dedicated location. To overcome these limitations, we propose a drone-based system, called "DermDrone," as an innovative concept for TBP. Firstly, a needs assessment procedure was conducted using off-the-shelf drones to recognize the user and device requirements. Afterward, the first MVP for DermDrone was proposed that offers an automated method for conducting TBP. The drone employs on-board real-time vision-based navigation using a customized floor map that allows it to follow a pre-defined trajectory around a patient and capture photos of all body parts. To improve the navigation method, this work proposes a human pose estimation (HPE)-based localization algorithm that provides positioning feedback with respect to the patient body without any external visual markers. Consequently, an RL -based method is implemented to enhance the accuracy of the proposed localization method by selecting the best viewpoint. Ultimately, an end-to-end RL-based navigation method is introduced in which DermDrone learns how to navigate around a patient using the result of HPE. The performances of both viewpoint selection and end-to-end navigation are shown with several experiments in simulation.
Document
Extent
182 pages.
Identifier
etd21763
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Arzanpour, Siamak
Language
English
Download file Size
etd21763.pdf 28.72 MB

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