
FOLLOWUS
1School of Control Science and Engineering, Shandong University, Jinan 250061, China
2School of Information Science and Engineering, Shandong University, Jinan 250100, China
E-mail:zhoufengyu@sdu.edu.cn
E-mail:yuanxianfeng_sdu@126.com
收稿:2015-08-21,
录用:2016-1-13,
纸质出版:2016-04
Scan QR Code
一种室内移动机器人高精度视觉定位传感器及其工作原理[J]. 信息与电子工程前沿(英文), 2016,17(4):365-374.
Feng-yu ZHOU, Xian-feng YUAN, Yang YANG, et al. A high precision visual localization sensor and its working methodology for an indoor mobile robot[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(4): 365-374.
一种室内移动机器人高精度视觉定位传感器及其工作原理[J]. 信息与电子工程前沿(英文), 2016,17(4):365-374. DOI: 10.1631/FITEE.1500272.
Feng-yu ZHOU, Xian-feng YUAN, Yang YANG, et al. A high precision visual localization sensor and its working methodology for an indoor mobile robot[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(4): 365-374. DOI: 10.1631/FITEE.1500272.
目的
2
高精度定位与导航是室内移动机器人高质量完成服务任务的基本前提。但现有的定位传感器大多难以满足服务机器人的室内定位精度要求。为了克服现有的移动机器人定位传感器定位精度低、鲁棒性差的问题,本文设计了一种基于红外反射人工标签的嵌入式视觉定位传感器,并提出了一种新颖的概率型视觉定位方法。
创新点
2
设计了一种高精度嵌入式视觉定位传感器,提出了一种概率型视觉定位方法。
方法
2
首先,设计了视觉定位传感器的硬件系统;然后,设计了一种红外反射标签,并给出了红外标签识别及置信度建模的方法;最后,利用P3P定位方法计算出机器人与红外标签的相对位置关系,并进一步解算得到机器人在世界坐标系下的位姿,实现了机器人高精度概率型视觉定位。
结论
2
通过多组实验证明了所设计的机器人定位传感器受光线及视角影响小,位置定位精度为±1.94 cm
角度定位精度为±1.64°,满足了室内移动机器人的定位精度要求。
To overcome the shortcomings of existing robot localization sensors
such as low accuracy and poor robustness
a high precision visual localization system based on infrared-reflective artificial markers is designed and illustrated in detail in this paper. First
the hardware system of the localization sensor is developed. Secondly
we design a novel kind of infrared-reflective artificial marker whose characteristics can be extracted by the acquisition and processing of the infrared image. In addition
a confidence calculation method for marker identification is proposed to obtain the probabilistic localization results. Finally
the autonomous localization of the robot is achieved by calculating the relative pose relation between the robot and the artificial marker based on the perspective-3-point (P3P) visual localization algorithm. Numerous experiments and practical applications show that the designed localization sensor system is immune to the interferences of the illumination and observation angle changes. The precision of the sensor is 1.94 cm for position localization and 1.64 for angle localization. Therefore
it satisfies perfectly the requirements of localization precision for an indoor mobile robot.
Y.D Aleksandrovich , , , P.G Gennadievich , , , K.A Stepanovich , , , 等 . . Mobile robot navigation based on artificial landmarks with machine vision system . . World Appl. Sci. J. , , 2013 . . 24 ( ( 11 ): ): 1467 - - 1472 . . . .
K.W Her , , , D.H Kim , , , J.E Ha . . Localization of mobile robot using laser range finder and IR landmark . . 2012 . . Proc. 12th Int. Conf. on Control, Automation and Systems . . 459 - - 461 . . . .
Y Kim , , , W.C Yoon . . Generating task-oriented interactions of service robots . . IEEE Trans. Syst. Man Cybern. , , 2014 . . 44 ( ( 8 ): ): 981 - - 994 . . DOI: 10.1109/TSMC.2014.2298214 http://doi.org/10.1109/TSMC.2014.2298214 . .
V Kroumov , , , K Okuyama . . Localisation and position correction for mobile robot using artificial visual landmarks . . Int. J. Adv. Mech. Syst. , , 2012 . . 4 ( ( 2 ): ): 112 - - 119 . . DOI: 10.1504/IJAMECHS.2012.048395 http://doi.org/10.1504/IJAMECHS.2012.048395 . .
W Lu , , , Z Xiang , , , J Liu . . Design of an enhanced visual odometry by building and matching compressive panoramic landmarks online . . Front. Inform. Technol. Electron. Eng. , , 2015 . . 16 ( ( 2 ): ): 152 - - 165 . . DOI: 10.1631/FITEE.1400139 http://doi.org/10.1631/FITEE.1400139 . .
Y Lu , , , D Song . . Visual navigation using heterogeneous landmarks and unsupervised geometric constraints . . IEEE Trans. Robot. , , 2015 . . 31 ( ( 3 ): ): 736 - - 749 . . DOI: 10.1109/TRO.2015.2424032 http://doi.org/10.1109/TRO.2015.2424032 . .
R.C Luo , , , O Chen . . Wireless and pyroelectric sensory fusion system for indoor human/robot localization and monitoring . . IEEE/ASME Trans. Mech. , , 2013 . . 18 ( ( 3 ): ): 845 - - 853 . . DOI: 10.1109/TMECH.2012.2188300 http://doi.org/10.1109/TMECH.2012.2188300 . .
R.C Luo , , , C.C Lai . . Multisensor fusion-based concurrent environment mapping and moving object detection for intelligent service robotics . . IEEE Trans. Ind. Electron. , , 2014 . . 61 ( ( 8 ): ): 4043 - - 4051 . . DOI: 10.1109/TIE.2013.2288199 http://doi.org/10.1109/TIE.2013.2288199 . .
J Mller , , , W Burgard . . Efficient probabilistic localization for autonomous indoor airships using sonar, air flow, and IMU sensors . . Adv. Robot. , , 2013 . . 27 ( ( 9 ): ): 711 - - 724 . . DOI: 10.1080/01691864.2013.779005 http://doi.org/10.1080/01691864.2013.779005 . .
T Nakamura , , , S Suzuki . . Simplified EKF-SLAM by combining laser range sensor with retro reflective markers for use in kindergarten . . Int. J. Robot. Mech. , , 2014 . . 1 ( ( 1 ): ): 1 - - 7 . . . .
J.H Oh , , , D Kim , , , B.H Lee . . An indoor localization system for mobile robots using an active infrared positioning sensor . . J. Ind. Intell. Inform. , , 2014 . . 2 ( ( 1 ): ): 35 - - 38 . . DOI: 10.12720/jiii.2.1.35-38 http://doi.org/10.12720/jiii.2.1.35-38 . .
S.M Persson , , , I Sharf . . Sampling-based A* algorithm for robot path-planning . . Int. J. Robot. Res. , , 2014 . . 33 ( ( 13 ): ): 1683 - - 1708 . . DOI: 10.1177/0278364914547786 http://doi.org/10.1177/0278364914547786 . .
M Reinstein , , , M Hoffmann . . Dead reckoning in a dynamic quadruped robot based on multimodal proprioceptive sensory information . . IEEE Trans. Robot. , , 2013 . . 29 ( ( 2 ): ): 563 - - 571 . . DOI: 10.1109/TRO.2012.2228309 http://doi.org/10.1109/TRO.2012.2228309 . .
Y Ren , , , A Ye , , , T Lu , , , 等 . . A method of selflocalization of robot based on infrared landmark . . 2014 . . Proc. 11th World Congress on Intelligent Control and Automation . . 5494 - - 5499 . . DOI: 10.1109/WCICA.2014.7053654 http://doi.org/10.1109/WCICA.2014.7053654 . .
M.S Sultan , , , X Chen , , , N Qadeer , , , 等 . . Vision guided path planning system for vehicles using infrared landmark . . 2013 . . Proc. IEEE Int. Conf. on Robotics and Biomimetics . . 179 - - 184 . . DOI: 10.1109/ROBIO.2013.6739455 http://doi.org/10.1109/ROBIO.2013.6739455 . .
M Vynnycky , , , K Kanev . . Mathematical analysis of the multisolution phenomenon in the P3P problem . . J. Math. Imag. Vis. , , 2015 . . 51 ( ( 2 ): ): 326 - - 337 . . DOI: 10.1007/s10851-014-0525-0 http://doi.org/10.1007/s10851-014-0525-0 . .
H Wu , , , G Tian , , , P Duan , , , 等 . . The design of a novel artificial label for robot navigation . . 2013 . . Proc. Chinese Intelligent Automation Conf. . . 479 - - 487 . . DOI: 10.1007/978-3-642-38460-8_53 http://doi.org/10.1007/978-3-642-38460-8_53 . .
D Xu , , , M Tan , , , Y Li . . Visual Measurement and Control for Robots , , 2011 . . : : National Defense Industry Press Beijing, China , , 132 - - 136 . . . .
H.H Yu , , , H.W Hsieh , , , Y.K Tasi , , , 等 . . Visual localization for mobile robots based on composite map . . J. Robot. Mech. , , 2013 . . 25 ( ( 1 ): ): 25 - - 37 . . . .
X Yuan , , , M Song , , , F Zhou , , , 等 . . A novel Mittag- Leffler kernel based hybrid fault diagnosis method for wheeled robot driving system . . Comput. Intell. Neurosci. , , 2015 . . 2015 606734 DOI: 10.1155/2015/606734 http://doi.org/10.1155/2015/606734 . .
Z Zhang . . A flexible new technique for camera calibration . . IEEE Trans. Patt. Anal. Mach. Intell. , , 2000 . . 22 ( ( 11 ): ): 1330 - - 1334 . . DOI: 10.1109/34.888718 http://doi.org/10.1109/34.888718 . .
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621