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Sensors 2014, 14(9), 16159-16180; doi:10.3390/s140916159

Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

1
Intelligent Vehicle Research Center, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 10081, China
2
Beijing Automotive Technology Center, Beijing 101300, China
3
Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT 84602, USA
*
Author to whom correspondence should be addressed.
Received: 23 July 2014 / Revised: 24 August 2014 / Accepted: 26 August 2014 / Published: 1 September 2014
(This article belongs to the Special Issue Positioning and Tracking Sensors and Technologies in Road Transport)
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Abstract

This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. View Full-Text
Keywords: monocular visual odometry; motion estimation; pose estimation; vehicle dynamic model; wheeled vehicles monocular visual odometry; motion estimation; pose estimation; vehicle dynamic model; wheeled vehicles
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Jiang, Y.; Xiong, G.; Chen, H.; Lee, D.-J. Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments. Sensors 2014, 14, 16159-16180.

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