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M-SLAM
Örebro University, School of Science and Technology, Örebro University, Sweden.
2015 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
M-SLAM (English)
Abstract [sv]

Examensarbetet går ut på att ta fram en metod för att minska osäkerheten i positionsbestämningen både utefter en magnetslinga och innanför magnetslingan, exempelvis en robotgräsklippare som har en magnetslinga. Data som man har tillgänglig är distansmätning, magnetfältstyrka och hjulströmmar, vilka alla har en osäkerhet i mätvärdet. Tillvägagångssättet är att formulera och lösa ett grafoptimeringsproblem. Men för att kunna utnyttja sig av ett grafoptimeringsproblem måste man vara säker på att kunna matcha sin position utefter magnetslingan. Det visades sig att det går att matcha sin position utefter magnetslingan med hjälp av mönsterigenkänning.

Abstract [en]

The aim of this thesis is to develop a method to reduce uncertainty in the determination

of the position, both along a magnetic perimeter line and inside the perimeter line loop. This problem is highly relevant for robotic lawnmowers. Data that is provided from the lawnmower is distance measurement, the magnetic eld strengths and the current from the electrical motors, which all have an uncertainty in the measurement. The approached used is to formulate and solve a graph optimization problems. However, to take advantage of a graph

optimization problem, one must be sure to be able to match position correctly along the magnetic perimeter line to assure that consistent measurements are used. In this work it is shown that it is possible to match the position along the magnetic perimeter line using pattern recognition.

Place, publisher, year, edition, pages
2015. , 30 p.
Keyword [en]
robotic mower, perimeter line, simulater in gazebo, pattern recognition, constraint network minimization problem, slam, ros, isam
Keyword [sv]
robotgräsklippare, magnetslinga, simulator i gazebo, mönsterigenkänning, grafoptimeringsproblem, slam, ros, isam
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:oru:diva-45659OAI: oai:DiVA.org:oru-45659DiVA: diva2:849075
Subject / course
Computer Engineering
Presentation
2015-06-01, T101, Örebro universitet, Fakultetsgatan 1, 702 81, Örebro, 09:15 (Swedish)
Supervisors
Examiners
Available from: 2015-08-27 Created: 2015-08-27 Last updated: 2016-12-13Bibliographically approved

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CiteExportLink to record
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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
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  • asciidoc
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