基于精简路标的机器人视觉归航算法

doi:10.13973/j.cnki.robot.2014.0751

摘要
图/表
参考文献
相关文章 (3)

全文: PDF (4556 KB) HTML ( ) 输出: BibTeX \| EndNote (RIS)
引用本文:
朱齐丹, 刘传家, 蔡成涛. 基于精简路标的机器人视觉归航算法[J]. 机器人, 2014, 36(6): 751-757,768.DOI: 10.13973/j.cnki.robot.2014.0751. ZHU Qidan, LIU Chuanjia, CAI Chengtao. A Robot Visual Homing Algorithm Based on Reduced Landmarks. ROBOT, 2014, 36(6): 751-757,768. DOI: 10.13973/j.cnki.robot.2014.0751.

摘要

在受生物导航方式启发的局部视觉归航算法中，ALV（average landmark vector）算法因其模型简单、归航性能较好以及所需存储空间小等优点受到了广泛的重视．在非结构化环境中，ALV算法常常需要使用图像的局部特征作为自然路标点，在这种情况下，路标的对应性问题难以保证，同时在保证归航性能的前提下如何合理地精简路标数量也尚无有效的解决方法．针对上述问题，对基于双曲面镜的折反射全景图像进行了研究，提出了horizon环域的概念．在环域内提取SIFT（scale invariant feature transform）特征作为自然路标点并结合ALV模型提出了一种改进的基于自然路标的ALV算法．改进算法有效地缩小了路标点的提取区域，较好地保证了路标点的对应性并精简了路标点的数量．多个实际场景的实验表明，这种算法有效提高了归航精度．

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	刘传家
	蔡成涛
	朱齐丹

关键词 ：视觉归航, 自然路标, 折反射全景图像, ALV算法

Abstract：

Among all the local visual homing algorithms inspired by the navigation of living creatures, ALV (average landmark vector) algorithm gains extensive attention for its simple model, better homing performance and less storage space, etc. In unstructured environments, ALV algorithm often uses local features of the image as natural landmarks. Under this circumstance, it is hard to ensure the correspondence of landmarks, at the same time, on the premise of ensuring its homing performance, there is no effective way to reduce the number of landmarks reasonably. In order to solve these problems, the concept of horizon ring-shaped region is put forward by the study on catadioptric panoramic image based on hyperboloidal mirror. An improved ALV algorithm based on natural landmarks is proposed by combining natural landmarks which are SIFT (scale invariant feature transform) features extracted from the ring-shaped region with ALV model. The improved algorithm effectively narrows the area for extracting landmarks and ensures the correspondence of landmarks, at the same time, it reduces the number of landmarks. Many experiments in different actual scenes indicate that the proposed algorithm improves homing precision effectively.

Key words： visual homing natural landmark catadioptric panoramic image ALV (average landmark vector) algorithm

收稿日期: 2014-04-10 录用日期: 2014-06-12

TP242.6

基金资助:

国家自然科学基金资助项目（61175089，61203255）；中央高校基本科研业务费专项基金资助项目（HEUCF1321001，HEUCFX41304）

通讯作者: 刘传家，b211040007@sina.com E-mail: b211040007@sina.com

作者简介: 朱齐丹（1963-），男，博士，教授．研究领域：智能机器人，机器视觉，先进控制理论及应用．
刘传家（1982-），男，博士．研究领域：机器人视觉，智能控制．
蔡成涛（1981-），男，博士，副教授．研究领域：计算机图像处理，全景视觉．

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.2014.0751 或 https://robot.sia.cn/CN/Y2014/V36/I6/751

[1] Yu S E, Kim D. Image-based homing navigation with landmark arrangement matching[J]. Information Sciences, 2011, 181(16): 3427-3442.

[2] Sturzl W, Zeil J. Depth, contrast and view-based homing in outdoor scenes[J]. Biological Cybernetics, 2007, 96(5): 519-531.

[3] Möller R, Krzykawski M, Gerstmayr L. Three 2D-warping schemes for visual robot navigation[J]. Autonomous Robots, 2010, 29(3/4): 253-291.

[4] Briggs A J, Detweiler C, Li Y P, et al. Matching scale-space features in 1D panoramas[J]. Computer Vision and Image Understanding, 2006, 103(3): 184-195.

[5] Hong J, Tan X, Pinette B, et al. Image-based homing[J]. IEEE Control Systems Magazine, 1992, 12(1): 38-45.

[6] Möller R. Local visual homing by warping of two-dimensional images[J]. Robotics and Autonomous Systems, 2009, 57(1): 87-101.

[7] 郑重,汪增福.基于随机搜索的快速变形视觉归巢算法[J].模式识别与人工智能,2010(5):593-600.Zheng Z, Wang Z F. A fast warping visual homing algorithm based on random search[J]. Pattern Recognition and Artificial Intelligence, 2010(5): 593-600.

[8] Basten K, Mallot H A. Simulated visual homing in desert ant natural environments: Efficiency of skyline cues[J]. Biological Cybernetics, 2010, 102(5): 413-425.

[9] Liu M, Pradalier C, Siegwart R. Visual homing from scale with an uncalibrated omnidirectional camera[J]. IEEE Transactions on Robotics, 2013, 29(6): 1353-1365.

[10] Yu S E, Kim D. Landmark vectors with quantized distance information for homing navigation[J]. Adaptive Behavior, 2011, 19(2): 121-141.

[11] 朱齐丹,李科,雷艳敏,等.基于全景视觉的机器人回航方法[J].机器人,2011,33(5):606-613.Zhu Q D, Li K, Lei Y M, et al. Robot homing based on panoramic vision[J]. Robot, 2011, 33(5): 606-613.

[12] 朱齐丹,刘学,蔡成涛.基于均匀分布特征的机器人归航[J].机器人,2013,35(5):544-551. Zhu Q D, Liu X, Cai C T. Robot homing with uniformly distributed features[J]. Robot, 2013, 35(5): 544-551.

[13] Lambrinos D, Möller R, Labhart T, et al. A mobile robot employing insect strategies for navigation[J]. Robotics and Autonomous Systems, 2000, 30(1/2): 39-64.

[14] Möller R. Insect visual homing strategies in a robot with analog processing[J]. Biological Cybernetics, 2000, 83(3): 231-244.

[15] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91-110.

[16] Ramisa A, Goldhoorn A, Aldavert D, et al. Combining invariant features and the ALV homing method for autonomous robot navigation based on panoramas[J]. Journal of Intelligent & Robotic Systems, 2011, 64(3/4): 625-649.

[17] Yu S E, Lee C M, Kim D E. Analyzing the effect of landmark vectors in homing navigation[J]. Adaptive Behavior, 2012, 20(5): 337-359.

[18] Franz M O, Scholkopf B, Mallot H A, et al. Where did I take that snapshot? Scene-based homing by image matching[J]. Biological Cybernetics, 1998, 79(3): 191-202.

[19] Vardy A, Möller R. Biologically plausible visual homing methods based on optical flow techniques[J]. Connection Science, 2005, 17(1/2): 47-89. 2005, 17(1/2): 47-89.