Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Orientation estimation and movement recognition using low cost sensors
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Orientation estimation is a very well known topic in many fields such as in aerospace or robotics. However, the sensors used are usually very ex- pensive, heavy and big, which make them not suitable for IoT (Internet of Things) based applications. This thesis presents a study of how different sensor fusion algorithms perform in low cost hardware and in high acceler- ation scenarios. For this purpose, an Arduino MKR1000 is used together with an accelerometer, gyroscope and magnetometer. The objective of the thesis is to choose the most suitable algorithm for the purposed practical application, which consists on attaching the device to a moving object, such as a skate board or a bike. Once the orientation is estimated, a movement recognition algorithm that was developed is able to match what trick or movement was performed. The algorithm chosen was the Madgwick one with some minor adjustments, which uses quaternions for the estimation and is very resilient when the device is under strong external accelerations.

Place, publisher, year, edition, pages
2017. , 79 p.
Keyword [en]
signal processing, orientation estimation, quaternion, euler angles, rotation matrices
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
Identifiers
URN: urn:nbn:se:bth-14949OAI: oai:DiVA.org:bth-14949DiVA: diva2:1127455
Subject / course
ET2566 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Signal processing
Educational program
ETASB Master of Science Programme in Electrical Engineering with emphasis on Signal Processing
Presentation
2017-06-12, BTH Gräsvis Campus, Karlskrona, 13:00 (English)
Supervisors
Examiners
Available from: 2017-08-01 Created: 2017-07-14 Last updated: 2017-08-01Bibliographically approved

Open Access in DiVA

fulltext(2591 kB)16 downloads
File information
File name FULLTEXT02.pdfFile size 2591 kBChecksum SHA-512
c1f8fa9176f7a2a791f5e000aa1363d14a85eea0b8879e29cb0eb8b0c4f284ad8ea53f6ee77c074d986f6fa26e14349b6c4f45c45218cb323ac72a68f5df82fd
Type fulltextMimetype application/pdf

By organisation
Department of Applied Signal Processing
Electrical Engineering, Electronic Engineering, Information EngineeringSignal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 16 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 146 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf