Stereo-Based Visual Odometry for Autonomous Robot Navigation

Ioannis Kostavelis*, Evangelos Boukas, Lazaros Nalpantidis, Antonios Gasteratos

*Kontaktforfatter

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

23 Citationer (Scopus)

Abstract

Mobile robots should possess accurate self-localization capabilities in order to be successfully deployed in their environment. A solution to this challenge may be derived from visual odometry (VO), which is responsible for estimating the robot's pose by analysing a sequence of images. The present paper proposes an accurate, computationally-efficient VO algorithm relying solely on stereo vision images as inputs. The contribution of this work is twofold. Firstly, it suggests a non-iterative outlier detection technique capable of efficiently discarding the outliers of matched features. Secondly, it introduces a hierarchical motion estimation approach that produces refinements to the global position and orientation for each successive step. Moreover, for each subordinate module of the proposed VO algorithm, custom non-iterative solutions have been adopted. The accuracy of the proposed system has been evaluated and compared with competent VO methods along DGPS-assessed benchmark routes. Experimental results of relevance to rough terrain routes, including both simulated and real outdoors data, exhibit remarkable accuracy, with positioning errors lower than 2%.

OriginalsprogEngelsk
Artikelnummer21
TidsskriftInternational Journal of Advanced Robotic Systems
Vol/bind13
Udgave nummer1
Antal sider19
ISSN1729-8806
DOI
StatusUdgivet - 10 feb. 2016

Emneord

  • Visual Odometry
  • Outlier Detection
  • Incremental Motion Estimation
  • Mobile Robots

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