hh.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Investigation of Cooperative SLAM for Low Cost Indoor Robots
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
2016 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

In robotics, SLAM is the problem of dynamically building a map while simultaneously using it to localize the robot. Most SLAM solutions rely on laser ranger devices or vision sensors (cameras). This work studies the possibility of extending current established SLAM solutions to low cost robotic platforms with few low quality short range distance sensors (Infrared and Sonar) and weak odometery information. This work starts by studying the performance of a low cost robotic platform `DiddyBorg' and build models for sensors and odometry to be used in SLAM implementation. Next, three SLAM solutions are implemented, tested and compared both in real environment and under simulation. The first two solutions are based on the well-established EKF-SLAM and RBPF-SLAM while the third is a custom simplified solution that is proposed in this work. The results show that RBPF-SLAM performed poorly compared to EKF-SLAM due to the limited sensory input affecting the quality of particles weighing scheme. The results also shows that while the sparsity of the sensors is a limiting factor on SLAM quality in general, the limited range of the sensors is a determinant factor on the overall convergence of SLAM. Finally, a simple map coding and merging algorithm is presented for evaluation of multi-robot collaborative SLAM, the solution enables a group of robots to collaborate on the SLAM tasks without any priori knowledge of the relative locations of robots.

sted, utgiver, år, opplag, sider
2016. , s. 93
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-31931OAI: oai:DiVA.org:hh-31931DiVA, id: diva2:958056
Fag / kurs
Computer science and engineering
Veileder
Examiner
Tilgjengelig fra: 2016-09-06 Laget: 2016-09-05 Sist oppdatert: 2016-09-06bibliografisk kontrollert

Open Access i DiVA

fulltext(19103 kB)546 nedlastinger
Filinformasjon
Fil FULLTEXT02.pdfFilstørrelse 19103 kBChecksum SHA-512
e817c5d2e52339117c755dacc4053dbb61a1fff051537f05fcf0f717c8e89b77e915399f6bbe5dfb9a8d4bea42a8b243145003ac10aa1e4cbf08bbc02a6c306f
Type fulltextMimetype application/pdf

Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar
Totalt: 546 nedlastinger
Antall nedlastinger er summen av alle nedlastinger av alle fulltekster. Det kan for eksempel være tidligere versjoner som er ikke lenger tilgjengelige

urn-nbn

Altmetric

urn-nbn
Totalt: 291 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf