Stereo-Based Visual Odometry for Autonomous Robot Navigation. (10th February 2016)

• Record Type: Journal Article
• Authors: Kostavelis, Ioannis; Boukas, Evangelos; Nalpantidis, Lazaros; Gasteratos, Antonios
• Is Part Of: International journal of advanced robotic systems. Volume 13:Number 1(2016)
• Publication Date: 2016-02-10
• Subjects: Visual Odometry -- Outlier Detection -- Incremental Motion Estimation -- Mobile Robots; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/62099
• Languages: English
• ISSNs: 1729-8806

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%.