Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
A Comparison of Path Planning Algorithms for Robotic Vacuum Cleaners
KTH, School of Electrical Engineering and Computer Science (EECS).
KTH, School of Electrical Engineering and Computer Science (EECS).
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
En jämförelse av ruttplaneringsalgoritmer för robotdammsugare (Swedish)
Abstract [en]

Household robotics is on the rise with robotic vacuum cleaners taking the lead. One of the challenges in creating great robotic vacuum cleaners is path planning for coverage of the room. For instance, the robot might not know how the environment looks, or where in the room the robot is. Three path planning algorithms are tested: the random path algorithm, the snaking algorithm and the spiral algorithm. In our simulations the random algorithm was initially faster than the snaking algorithm. However, the random algorithm's performance worsened and it performed similar to the snaking algorithm in the end. The spiral algorithm performed worse than the other tested algorithms. The random algorithm showed a more stable performance than both the snaking and spiral algorithms. However, we believe that the spiral algorithm could be complemented with other algorithms. Errors in the results could possibly come from the method used in the software to detect wall collisions. Future research could improve the software and also cover collision with objects in rooms and rooms of other shapes. We concluded that the random algorithm performed best in our simulations and questioned the practical use of more advanced algorithms.

Abstract [sv]

Antalet robotar i hemmet ökar i världen och robotdammsugaren är ett populärt val. Bra ruttplaneringsalgoritmer är en av utmaningarna för att tillverka bra robotdammsugare. Exempelvis behöver inte roboten känna till sin position i ett rum eller ens känna till rummets utseende, hur ska utvecklare gå till väga? Tre ruttplaneringsalgoritmer har testats: en slumpartad algoritm, en sicksack-algoritm och en spiral-algoritm. I våra simuleringar fann vi att den slumpartade algoritmen var initialt snabbare än sicksack-algoritmen. Dock försämrades slumpalgoritmen över tid och till slut gav result likt de vi såg för sicksack-algoritmen. Spiral-algoritmen gav sämre resultat än de två övriga testade algoritmerna. Slumpalgoritmen hade mindre avvikelse än både spiral-algoritmen och sicksack-algoritmen. Vi tror att spiral-algoritmen skulle kunna kombineras med andra algoritmer för att ge bättre resultat. Fel i våra resultat kan bero på hur vi upptäcker väggkollisioner i simuleringarna. Framtida forskning kan förbättra och utveckla mjukvaran samt testa rum med varierande utseende. Sammanfattningsvis var slumpalgoritmen bäst i våra simuleringar och vi ifrågasätter den praktiska användbarheten hos andra mer avancerade algoritmer.

Place, publisher, year, edition, pages
2018.
Series
TRITA-EECS-EX ; 2018:185
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-229771OAI: oai:DiVA.org:kth-229771DiVA, id: diva2:1214422
Subject / course
Computer Science
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2018-06-26 Created: 2018-06-06 Last updated: 2018-06-26Bibliographically approved

Open Access in DiVA

fulltext(660 kB)35 downloads
File information
File name FULLTEXT01.pdfFile size 660 kBChecksum SHA-512
a8fc82252bc84c0c44fe04522f8a0a9171ec9f17ca9838aeeac145cb51f3d0e4c099597cc62154a334a109765e27dcc27097116f97ae20a5f5af0f076d3052d1
Type fulltextMimetype application/pdf

By organisation
School of Electrical Engineering and Computer Science (EECS)
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 35 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

urn-nbn

Altmetric score

urn-nbn
Total: 32 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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