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面向小型机器人的超大视场红外立体视觉可行性分析

Analysis on Feasibility of Infrared Ultrawide FOV Binocular Vision for Small Robots

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摘要

小型机器人传统视觉方法对环境适应性差。提出了一种基于双目超大视场红外相机的环境感知方法。利用大视场镜头高阶奇次多项式模型, 建立了超大视场红外双目立体成像的水平和垂直视差数字模型。以视差模型为基础建立超大视场红外双目视觉模型, 研究了超大视场红外双目系统立体视觉范围和阈值。搭建了视场为170°×128°的超大视场红外立体视觉系统, 分析了立体视觉范围及阈值应用于小型机器人视觉的可行性。同时, 针对照度不均、雾霾等条件下的场景开展超大视场红外双目立体视觉实验研究, 构建了双目图像标准视差图, 结果表明, 超大视场红外双目立体视觉系统对复杂场景具有良好的适应性, 基本能够满足小型机器人视觉系统需求。

Abstract

To overcome such defects as poor environmental adaptability of traditional machine vision, a kind of environmental perception method based on binocular infrared ultrawide field of view (FOV) camera was proposed. Horizontal and vertical models for ultrawide FOV binocular infrared imaging were established by using high order polynomial model. Stereo vision range and threshold were researched on the basis of parallax model. Infrared ultrawide FOV binocular stereo vision system with the vision field of 170°×128° was established. Stereo vision experiments were carried out under different conditions, such as uneven illumination, smog, etc. Subjective and objective evaluation shows that infrared ultrawide FOV binocular stereo vision system has good applicability to complex scenes and is able to realize 3D depth perception of the infrared ultrawide FOV, which basically meets the requirements of small robot vision system.

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中图分类号:TP394.1

DOI:10.16818/j.issn1001-5868.2019.02.025

所属栏目:光电技术及应用

基金项目:国家自然科学基金项目(61801507)

收稿日期:2018-11-21

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作者单位    点击查看

陈一超:陆军工程大学石家庄校区 电子与光学工程系, 石家庄 050003
刘秉琦:陆军工程大学石家庄校区 电子与光学工程系, 石家庄 050003
黄富瑜:陆军工程大学石家庄校区 电子与光学工程系, 石家庄 050003

联系人作者:陈一超(opticscyc@163.com)

备注:陈一超(1991-), 男, 博士研究生, 主要从事光电对抗和光电检测方面的研究。

【1】刘 斌. 四足机器人落地过程中缓冲策略的研究[D]. 济南: 山东大学, 2017.
Liu Bin. Study on buffering strategy in landing process of a quadruped robot[D]. Jinan: Shandong University, 2017.

【2】Ramón González, Alejandro López, Iagnemma K. Thermal vision, moisture content and vegetation in the context of offroad mobile robots[J]. J. of Terramechanics, 2017, 70: 3548.

【3】Min Q, Huang Y. Motion detection using binocular image flow in dynamic scenes[J]. Eurasip J. on Advances in Signal Proc., 2016(1): 49.

【4】王 科. 城市交通中智能车辆环境感知方法研究[D]. 长沙: 湖南大学, 2013.
Wang Ke. Environment perception menthod of intelligent vehicle in urban traffic[D]. Changsha: Hunan University, 2013.

【5】宋 涛, 熊文莉, 侯培国, 等. 基于极曲线几何和支持邻域的鱼眼图像立体匹配[J]. 光学精密工程, 2016, 24(8): 20502058.
Song Tao, Xiong Wenli, Hou Peiguo, et al. Stereo matching for fisheye images based on epipolar geometry and support neighborhood[J]. Optics and Precision Engin., 2016, 24(8): 20502058.

【6】王永仲. 鱼眼镜头光学[M]. 北京: 科学出版社, 2006: 3440.
Wang Yongzhong. Fish Eye Lens Optics[M]. Beijing: Science Press, 2006: 3440.

【7】李海滨, 褚光宇, 张 强, 等. 基于优化的角眼镜头成像模型的空间点定位[J]. 光学学报, 2015, 35(7): 247253.
Li Haibin, Chu Guangyu, Zhang Qiang, et al. Space point positioning based on optimization of fisheye lens imaging model[J], Acta Optica Sinica, 2015, 35(7): 247253.

【8】Kannala J, Brandt S S. A generic camera model and calibration method for conventional, wideangle and fisheye lenses[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2006, 28(8): 13351340.

【9】汪同浩, 刘秉琦, 陈一超, 等. 平行式双目立体系统基线长度的选取[J]. 半导体光电, 2017, 38(4): 614617.
Wang Tonghao, Liu Bingqi, Chen Yichao, et al. Selection of baseline length for parallel binocular stereo system[J]. Semiconductor Optoelectronics, 2017, 38(4): 614617.

【10】Scaramuzza D. A flexible technique for accurate omnidirectional camera calibration and structure from motion[J]. IEEE Computer Vision Systems, 2006: 4552.

【11】张以谟. 应用光学[M]. 北京: 电子工业出版社, 2008: 384385.
Zhang Yimo. Applied Optics[M]. Beijing: Publishing House of Electronics Industry, 2008: 384385.

【12】Kim Deukhyeon, Choi Jinwook, Yoo Hunjae, et al. Rear obstacle detection system with fisheye stereo camera using HCT[J]. Expert Systems with Applications, 2015, 42(17): 62956305.

【13】Zhai Zhiqiang, Zhu Zhongxiang, Du Yuefeng, et al. Multicroprow detection algorithm based on binocular vision[J]. Biosystems Engin., 2016, 150(1): 89103.

引用该论文

CHEN Yichao,LIU Bingqi,HUANG Fuyu. Analysis on Feasibility of Infrared Ultrawide FOV Binocular Vision for Small Robots[J]. Semiconductor Optoelectronics, 2019, 40(2): 266-270

陈一超,刘秉琦,黄富瑜. 面向小型机器人的超大视场红外立体视觉可行性分析[J]. 半导体光电, 2019, 40(2): 266-270

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