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Motion planning for mobile robot navigation using combine quad-tree decomposition and Voronoi diagrams

  • Shahed Shojaeipour
  • , Sallehuddin Mohamed Haris
  • , Khalil Khalili
  • , Ali Shojaeipour

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

This paper presents a novel method for mobile robot navigation by visual environments where there are obstacles in the workspace. The method uses a path selection mechanism that creates innovative paths through the workspace and learns to use trajectory that are more assured. This approach is implemented on motion robots which verified the shortest path via Quad-tree Decomposition (QD) and then used Voronoi Diagrams (VD(S)) algorithm we called (Q&V) algorithm. Based on the experimental data, we claim the robot's trajectory planned by Q&V algorithm is the better find and control the roadmap is completely modeled and hasn't the localization errors. We show that even small modeled obstacles can cause large used from the preplanned path. Our complementary approach of path selection decreases the risk of path following and increases the predictability of robot's behavior.

Original languageEnglish
Title of host publication2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
Pages90-93
Number of pages4
DOIs
Publication statusPublished - 19 Apr 2010
Externally publishedYes
Event2nd International Conference on Computer and Automation Engineering, ICCAE 2010 - Singapore, Singapore
Duration: 26 Feb 201028 Feb 2010

Publication series

Name2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
Volume1

Conference

Conference2nd International Conference on Computer and Automation Engineering, ICCAE 2010
Country/TerritorySingapore
CitySingapore
Period26/02/1028/02/10

Keywords

  • Mobile robot
  • Motion planning
  • Obstacle avoidance
  • Q&V
  • Quad-tree
  • Visual servo

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