NDLI: Real-time Visual Odometry Estimation Based on Principal Direction Detection on Ceiling Vision

Content Provider	Springer Nature Link
Author	Wang, Han Mou, Wei Seet, Gerald Li, Mao Hai Lau, M. W. S. Wang, Dan Wei
Copyright Year	2013
Abstract	In this paper, we present a novel algorithm for odometry estimation based on ceiling vision. The main contribution of this algorithm is the introduction of principal direction detection that can greatly reduce error accumulation problem in most visual odometry estimation approaches. The principal direction is defined based on the fact that our ceiling is filled with artificial vertical and horizontal lines which can be used as reference for the current robot’s heading direction. The proposed approach can be operated in real-time and it performs well even with camera’s disturbance. A moving low-cost RGB-D camera (Kinect), mounted on a robot, is used to continuously acquire point clouds. Iterative closest point (ICP) is the common way to estimate the current camera position by registering the currently captured point cloud to the previous one. However, its performance suffers from data association problem or it requires pre-alignment information. The performance of the proposed principal direction detection approach does not rely on data association knowledge. Using this method, two point clouds are properly pre-aligned. Hence, we can use ICP to fine-tune the transformation parameters and minimize registration error. Experimental results demonstrate the performance and stability of the proposed system under disturbance in real-time. Several indoor tests are carried out to show that the proposed visual odometry estimation method can help to significantly improve the accuracy of simultaneous localization and mapping (SLAM).
Starting Page	397
Ending Page	404
Page Count	8
File Format	PDF
ISSN	14768186
Journal	International Journal of Automation and Computing
Volume Number	10
Issue Number	5
e-ISSN	17518520
Language	English
Publisher	Springer-Verlag
Publisher Date	2014-05-22
Publisher Place	London
Access Restriction	Subscribed
Subject Keyword	Visual odometry ego-motion principal direction ceiling vision simultaneous localization and mapping (SLAM) Control, Robotics, Mechatronics Computer Applications Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Control and Systems Engineering Modeling and Simulation Computer Science Applications

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