当前位置: X-MOL 学术IEEE Intell. Transp. Syst. Mag. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Positioning Accuracy Improvement of Automated Guided Vehicles Based on a Novel Magnetic Tracking Approach
IEEE Intelligent Transportation Systems Magazine ( IF 3.6 ) Pub Date : 2020-01-01 , DOI: 10.1109/mits.2018.2880269
Shijian Su , Xianping Zeng , Shuang Song , Mingqiang Lin , Houde Dai , Wanan Yang , Chao Hu

Automated guided vehicles (AGVs) have been widely adopted in the logistic delivering of modern manufacturing. As a key performance index for an AGV, the positioning accuracy of commercial AGVs based on the traditional magnetic tracking approach is bigger than ?5mm, which cannot meet the requirement of many industrial applications. Thus, we proposed a novel magnetic tracking approach to improve the positioning accuracy of AGVs. A super strong magnetic nail, instead of the low-remanence magnetic nail, can be more easily tracked by a two-dimensional (2D) rather than 1 D sensor array. The magnetic flux intensity around the magnetic nail can be expressed as a dipole model. Hence, the location and orientation of the nail can be computed via the sensor array data and a hybrid optimization algorithm, which is combined by the particle swarm optimization (PSO) algorithm and Levenberg-Marquardt (LM) algorithm performed on a microcontroller. We carried out experiments to verify the performance of the proposed positioning system in a series of initial driving speeds and target distances, where an N35 neodymium magnetic nail functioned as the designated AGV positioning point. Results show that the average positioning accuracy is improved to ?1.69mm, and the positioning accuracy can be further improved by a better motion control strategy. In addition, our proposed magnetic tracking approach can be easily fused with other navigation approaches such as laser and inertial sensing.

中文翻译:

基于新型磁跟踪方法提高自动导引车定位精度

自动导引车 (AGV) 已广泛应用于现代制造业的物流配送。作为AGV的关键性能指标,基于传统磁跟踪方式的商用AGV定位精度大于±5mm,无法满足很多工业应用的要求。因此,我们提出了一种新的磁跟踪方法来提高 AGV 的定位精度。一个超强磁钉,而不是低剩磁磁钉,可以更容易地被二维(2D)而不是一维传感器阵列跟踪。磁钉周围的磁通强度可以表示为偶极子模型。因此,可以通过传感器阵列数据和混合优化算法计算指甲的位置和方向,它由在微控制器上执行的粒子群优化 (PSO) 算法和 Levenberg-Marquardt (LM) 算法相结合。我们进行了实验以验证所提出的定位系统在一系列初始行驶速度和目标距离下的性能,其中 N35 钕磁钉用作指定的 AGV 定位点。结果表明,平均定位精度提高到±1.69mm,通过更好的运动控制策略可以进一步提高定位精度。此外,我们提出的磁跟踪方法可以很容易地与其他导航方法(如激光和惯性传感)融合。我们进行了实验以验证所提出的定位系统在一系列初始行驶速度和目标距离下的性能,其中 N35 钕磁钉用作指定的 AGV 定位点。结果表明,平均定位精度提高到±1.69mm,通过更好的运动控制策略可以进一步提高定位精度。此外,我们提出的磁跟踪方法可以很容易地与其他导航方法(如激光和惯性传感)融合。我们进行了实验以验证所提出的定位系统在一系列初始行驶速度和目标距离下的性能,其中 N35 钕磁钉用作指定的 AGV 定位点。结果表明,平均定位精度提高到±1.69mm,通过更好的运动控制策略可以进一步提高定位精度。此外,我们提出的磁跟踪方法可以很容易地与其他导航方法(如激光和惯性传感)融合。
更新日期:2020-01-01
down
wechat
bug