A neural inspired grid cell aid for robot intertial navigation.

Simple item page
dc.contributor.advisorKoziol, Scott M.
dc.creatorMartinez, Moises, 1993-
dc.date.accessioned2018-05-30T13:19:31Z
dc.date.available2018-05-30T13:19:31Z
dc.date.created2018-05
dc.date.issued2018-05-08
dc.date.submittedMay 2018
dc.date.updated2018-05-30T13:19:31Z
dc.description.abstractAccurate position information is needed for a robot's guidance and control systems. Therefore, the navigation system is foundational for a robot's interactions with the world. This thesis explores a biologically inspired method of navigation with the goal of improving navigational accuracy. The desire to integrate brain-inspired methods with conventional signal processing methods is based on animals' innate ability to successfully navigate through habitats. Therefore, it is reasonable to explore the way animals process brain signals to navigate and leverage it for robot navigation. This thesis uses a combinatorial model of map formation and localization with grid cells to aid dead reckoning with an accelerometer and gyroscope to show grid cells are a viable aid in idiothetic navigation. The results show that the grid cell aided navigation systems shows better performance with longer paths and higher noise values with an improvement of 57.24 cm for a 32 m path with 3 σ noise.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2104/10359
dc.language.isoen
dc.rights.accessrightsWorldwide access.
dc.rights.accessrightsAccess changed 9/25/23.
dc.subjectGrid cells. Navigation. Inertial navigation system. Vector navigation. Comparison. Analysis.
dc.titleA neural inspired grid cell aid for robot intertial navigation.
dc.typeThesis
dc.type.materialtext
local.embargo.lift2023-05-01
local.embargo.terms2023-05-01
thesis.degree.departmentBaylor University. Dept. of Electrical & Computer Engineering.
thesis.degree.grantorBaylor University
thesis.degree.levelMasters
thesis.degree.nameM.S.E.C.E.

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
MARTINEZ-THESIS-2018.pdf
Size:
1.64 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
ETDAgreement082017_M_Martinez_rev3.pdf
Size:
209.49 KB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.95 KB
Format:
Plain Text
Description:
Download

Collections

Electronic Theses and Dissertations
Theses/Dissertations - Electrical and Computer Engineering