Monocular Vision Obstacle Detection Method Based on Radial Optical Flow for Rotor UAV

doi:10.11947/j.AGCS.2017.20160510

Abstract

Abstract: To solve the problem of traditional Pyramid LK optical flow algorithm's poor accuracy and adaptability for rotor UAV to detect obstacle in complex outdoor environment, a monocular autonomous real-time obstacle detection method based on radial optical flow is proposed. In the optical flow, the radial optical flow is computed by fusing Pyramid LK optical flow with tangential optical flow, and a new obstacles decision strategy to detect obstacles based on the radial optical flow is put forward. Experimental results show that without increasing the complexity of algorithm, the proposed method can get a higher accuracy and better adaptability than traditional Pyramid LK algorithm, which can meet the requirements of UAV autonomous obstacle avoidance.

Key words: rotor UAV, monocular vision, obstacle detection, radial optical flow, Pyramid LK optical flow, tangential optical flow

CLC Number:

P235

ZHANG Xiaodong, HAO Xiangyang, SUN Guopeng, XU Yali. Monocular Vision Obstacle Detection Method Based on Radial Optical Flow for Rotor UAV[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(9): 1107-1115.

References

[1] REINEMAN B D, LENAIN L, STATOM N M, et al. Development and Testing of Instrumentation for UAV-based Flux Measurements within Terrestrial and Marine Atmospheric Boundary Layers[J]. Journal of Atmospheric and Oceanic Technology, 2013, 30(7):1295-2954.
[2] 马源. 基于双目立体视觉的深度感知技术研究[D]. 北京:北京理工大学, 2015. MA Yuan. Research on Depth Perception Based on the Binocular Stereo Vision[D]. Beijing:Beijing Institute of Technology, 2015.
[3] CHAO Haiyang, CAO Yongcan, CHEN Yangquan. Autopilots for Small Unmanned Aerial Vehicles:A Survey[J]. International Journal of Control, Automation and Systems, 2010, 8(1):36-44.
[4] ZINGG S, SCARAMUZZA D, WEISS S, et al. MAV Navigation through Indoor Corridors Using Optical Flow[C]//Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA). Anchorage, AK:IEEE, 2010:3361-3368.
[5] LIYANAGE D K, PERERA M U S. Optical Flow Based Obstacle Avoidance for the Visually Impaired[C]//Proceedings of the 2012 IEEE Business Engineering and Industrial Applications Colloquium (BEIAC). Kuala Lumpur:IEEE, 2012:284-289.
[6] LIAU Y S, ZHANG Qun, LI Yanan, et al. Non-metric Navigation for Mobile Robot Using Optical Flow[C]//Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vilamoura:IEEE, 2012:4953-4958.
[7] SRINIVASAN M V, MOORE R J D, THURROWGOOD S, et al. From Biology to Engineering:Insect Vision and Applications to Robotics[M]//BARTH F G, HUMPHREY J A C, SRINIVASAN M V. Frontiers in Sensing. Vienna:Springer, 2012:19-39.
[8] 徐伟杰. 基于视觉的微小型无人直升机位姿估计与目标跟踪研究[D]. 杭州:浙江大学, 2012. XU Weijie. Research on Vision-based Pose Estimation and Object Tracking for Miniature Unmanned Helicopter[D]. Hangzhou:Zhejiang University, 2012.
[9] 赵海, 陈星池, 王家亮, 等. 基于四轴飞行器的单目视觉避障算法[J]. 光学精密工程, 2014, 22(8):2232-2241. ZHAO Hai, CHEN Xingchi, WANG Jialiang, et al. Obstacle Avoidance Algorithm Based on Monocular Vision for Quad-rotor Helicopter[J]. Optics and Precision Engineering, 2014, 22(8):2232-2241.
[10] ERESEN A, I·MAMOǦLU N, ÖNDER EFE M. Autonomous Quad Rotor Flight with Vision Based Obstacle Avoidance in Virtual Environment[J]. Expert Systems with Applications, 2012, 39(1):894-905.
[11] 易礼智. 基于机器视觉的避障智能小车系统研究[D]. 长沙:中南大学, 2012. YI Lizhi. Research on Obstacle Avoidance Smart Car System Based on Machine Vision[D]. Changsha:Central South University, 2012.
[12] 郑海华. 基于视觉的平地探测机器人避障研究[D]. 长沙:中南大学, 2014. ZHENG Haihua. Research on Obstacle Avoidance of Flat Detection Robot Based on Vision[D]. Changsha:Central South University, 2014.
[13] 刘正东, 高鹏, 杨静宇. 一种用于道路避障的双目视觉图像分割方法[J]. 计算机应用研究, 2005, 22(4):249-251. LIU Zhengdong, GAO Peng, YANG Jingyu. Binocular Image Segmentation Algorithm for Obstacles Avoidance[J]. Application Research of Computers, 2005, 22(4):249-251.
[14] KENDOUL F, FANTONI A, NONAM A. Optic Flow-based Vision System for Autonomous 3D Localization and Control of Small Aerial Vehicles[J]. Robotics and Autonomous Systems, 2009, 57(6-7):591-602.
[15] GRIGORESCU S M, MACESANU G, COCIAS T T, et al. Robust Camera Pose and Scene Structure Analysis for Service Robotics[J]. Robotics and Autonomous Systems, 2011, 59(11):889-909.
[16] VO V, LY N. An Effective Approach for Human Actions Recognition Based on Optical Flow and Edge Features[C]//Proceedings of the 2012 International Conference on Control, Automation and Information Sciences (ICCAIS). Ho Chi Minh City:IEEE, 2012:24-29.
[17] CHATTERJEE A, RAKSHIT A, SINGH N N. 基于视觉的自主机器人导航[M]. 连晓峰, 译. 北京:机械工业出版社, 2014. CHATTERJEE A, RAKSHIT A, SINGH N N. Vision Based Autonomous Robot Navigation[M]. LIAN Xiaofeng, trans. Beijing:Machinery Industry Press, 2014.
[18] 张正鹏, 江万寿, 张靖. 自适应运动结构特征的车载全景序列影像匹配方法[J]. 测绘学报, 2015, 44(10):1132-1141. DOI:10.11947/j.AGCS.2015.20140622. ZHANG Zhengpeng, JIANG Wanshou, ZHANG Jing. An Matching Method for Vehicle-borne Panoramic Image Sequence Based on Adaptive Structure from Motion Feature[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(10):1132-1141. DOI:10.11947/j.AGCS.2015.20140622.
[19] BRADSKI G, KAEHLER A. 学习OpenCV[M]. 于仕琪, 刘瑞祯, 译. 北京:清华大学出版社, 2009:358-366. BRADSKI G, KAEHLER A. Learning OpenCV[M]. YU Shiqi, LIU Ruizhen, trans. Beijing:Tsinghua University Press, 2009:358-366.
[20] 李佳田, 李显凯, 李应芸, 等. 航空图像光流场的逆向金字塔计算方法[J]. 测绘学报, 2016, 45(9):1059-1064. DOI:10.11947/j.AGCS.2016.20150367. LI Jiatian, LI Xiankai, LI Yingyun, et al. A Backward Pyramid Oriented Optical Flow Field Computing Method for Aerial Image[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(9):1059-1064. DOI:10.11947/j.AGCS.2016.20150367.
[21] HARTLEY R, ZISSERMAN A. Multiple View Geometry in Computer Vision[M]. Cambridge:Cambridge University Press, 2004.
[22] EBERLI D, SCARAMUZZA D, WEISS S, et al. Vision Based Position Control for MAVs Using One Single Circular Landmark[J]. Journal of Intelligent & Robotic System, 2011, 61(1-4):495-512.
[23] HARTLEY R, ZISSERMAN A. 计算机视觉中的多视图几何[M]. 韦穗, 杨尚骏, 章权兵, 译. 合肥:安徽大学出版社, 2002. HARTLEY R, ZISSERMAN A. Multiple View Geometry in Computer Vision[M]. WEI Hui, YANG Shangjun, ZHANG Quanbing, trans. Hefei:Anhui University Press, 2002.
[24] 崔燕茹. 基于双目视觉的障碍物识别与重建[D]. 南昌:南昌航空大学, 2012. CUI Yanru. Obstacle Recognition and Reconstruction Based on Binocular Vision[D]. Nanchang:Nanchang Hangkong University, 2012.
[25] STEFANOSKI N, WANG O, LANG M, et al. Automatic View Synthesis by Image-domain-warping[J]. IEEE Transactions on Image Processing, 2013, 22(9):3329-3341.
[26] 夏军营, 徐小泉, 熊九龙. 利用平行透视投影模型的位姿迭代估计[J]. 光学精密工程, 2012, 20(6):1342-1349. XIA Junying, XU Xiaoquan, XIONG Jiulong. Iterative Pose Estimation Using Paraperspective Camera Model[J]. Optics and Precision Engineering, 2012, 20(6):1342-1349.
[27] 戴碧霞. 基于光流的微小型飞行器室内避障方法研究[D]. 成都:电子科技大学, 2015. DAI Bixia. Research on Obstacle Avoidance Method of MAV in Indoor Environment Based on Optical Flow[D]. Chengdu:University of Electronic Science and Technology of China, 2015.