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Sensors 2015, 15(11), 29594-29617;

Vision Sensor-Based Road Detection for Field Robot Navigation

College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, Hunan, China
Author to whom correspondence should be addressed.
Academic Editors: Lianqing Liu, Ning Xi, Wen Jung Li, Xin Zhao and Yajing Shen
Received: 21 September 2015 / Revised: 13 November 2015 / Accepted: 17 November 2015 / Published: 24 November 2015
(This article belongs to the Special Issue Sensors for Robots)
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Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. View Full-Text
Keywords: robot navigation; road detection; MPGA; GrowCut; conditional random field robot navigation; road detection; MPGA; GrowCut; conditional random field

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Lu, K.; Li, J.; An, X.; He, H. Vision Sensor-Based Road Detection for Field Robot Navigation. Sensors 2015, 15, 29594-29617.

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