In the field of unmanned transportation, the parking position of AGV trolley is not accurate enough when docking at the workstation.This paper uses lidar and depth camera sensors, and through the corresponding coordinate transformation, measures the distance of obstacles and obtains the sensor.Through the selection of the appropriate transfer function and learning algorithm, the RBF neural network is used for training, and the simulation verification results show that the range error of the result obtained by this method is less than 0.1%, and the speed is compared with the traditional BP algorithm.It is increased by 24%, which can be used to assist the relocation of the AGV trolley when it is parked.At the same time, the data obtained through fusion also has certain advantages in future mapping.
Key words
unmanned transportation /
RBF neural network /
lidar /
vision camera /
data fusion
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References
[1] 战艺.移动机器人SLAM 与路径规划方法研究[D].桂林:广西大学, 2016.
[2] LEE D H, CHANG J, YHEO Y S.Stereo matching using cost volume fusion for high dynamic range scenes[J].Electronics Letters, 2017, 53(23):15221524.
[3] ZHAO X, KAN J.A trunk ranging system based on binocular stereo vision[C]//The 9th International Conference on Digital Image Processing (ICDIP 2017) International Society for Optics and Photonics, 2017:10431048.
[4] 刘坤, 翟敬梅.室内阴影环境下障碍物检测与测量[J].计算机工程与设计, 2017(10):27992803.
[5] 卢艳军, 王诗宇, 张太宁, 等.针对目标跟踪过程的双目视觉测距方法研究[J].电光与控制, 2020, 27(1) :6063.
[6] 李大华, 沈洪宇, 于晓, 等.一种改进Census变换的双目匹配测距方法[J].激光与光电子学进展, 2019, 56(11):189194.
[7] SHANG E, AN X, WU T, et al.Li DAR based negativeobstacledetectionfor field autonomous land vehicles[J].Journal of Field Robotics, 2016, 33(5):591617.
[8] 刘家银, 唐振民, 王安东, 等基于多激光雷达与组合特征的非结构化环境负障碍物检测[J].机器人, 2017, 39(5):638651.
[9] 孙贝贝.基于异质传感器信息融合的移动机器人避障研究[D].太原:中北大学, 2018.
[10] 李蔚东, 谢再晋, 李敏.基于多传感器融合的扫地机器人算法研究[J].电子设计工程, 2021, 29(2):118122, 128.
[11] FETIC A, JURIC D, OSMANKOVIC D.The procedure of a camera calibration using camera calibration toolbox for Matlab[C]//MIPRO Proceedings of the 35th International Convention IEEE, 2012:17521757.
[12] 周鹏程.基于机器视觉的自主式救援机器人的研究[D].南京:东南大学, 2016.
[13] 王中立, 牛颖.基于多传感器信息融合的机器人障碍物检测[J].中国测试, 2017, 43(8): 8085.
[14] 黄琴.基于贝叶斯估计与分布的关联分析方法研究[D].广州:华南理工大学, 2016.
[15] 张春英, 冯晓泽, 刘凤春, 等.基于DS证据理论的三支决策推理模型[J].模糊系统与数学, 2020, 34(6).
[16] Liu Q, Wang X, Rao N S V.Artificial neural netwoksfor estimation and fusion in longhaul sensor networks[C]//International Conference on Information Fusion, 2015:460467.
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