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Robot Assisted Bed Bathing For People with Severe Mobility Limitations

dc.contributor.authorValdez, Skyler
dc.contributor.chairBhattacharjee, Tapomayukhen_US
dc.contributor.committeeMemberCampbell, Marken_US
dc.date.accessioned2024-04-05T18:36:50Z
dc.date.issued2023-08
dc.description55 pagesen_US
dc.description.abstractDeveloping a robot assisted bed bathing system requires the integration of a diverse range of abilities including perception of the area to be cleaned, planning of a trajectory for wiping across this region of interest, and executing this task in a safe and reliable manner. To accomplish this, we curated a bed bathing dataset using a manikin arm and trained a multimodal perception network capable of leveraging thermal and RGB image data to segment water, soap, and dry skin. Given the results of this segmentation, we demonstrated the ability to clean over the perceived soap, water, and dry regions while ensuring safety through compliance in both the hardware and controls. Limb repositioning is a natural expansion upon this problem as it would allow for washing of hard to reach areas such as under the arm. We can represent this task as an active manipulator moving a passive arm by a fixed grasp point and formulate a dynamics model which can then be used to predict the states of the robot and human arm given a torque command to the robot. In this thesis, this model is verified in simulation (PyBullet) and future work is discussed in the context of assisted bathing.en_US
dc.identifier.doihttps://doi.org/10.7298/zbet-c425
dc.identifier.otherValdez_cornell_0058O_11876
dc.identifier.otherhttp://dissertations.umi.com/cornell:11876
dc.identifier.urihttps://hdl.handle.net/1813/114526
dc.language.isoen
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectAssistiveen_US
dc.subjectMachine Learningen_US
dc.subjectRoboticsen_US
dc.titleRobot Assisted Bed Bathing For People with Severe Mobility Limitationsen_US
dc.typedissertation or thesisen_US
dcterms.licensehttps://hdl.handle.net/1813/59810.2
thesis.degree.disciplineComputer Science
thesis.degree.grantorCornell University
thesis.degree.levelMaster of Science
thesis.degree.nameM.S., Computer Science

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