自动导引车模型设计

 自动导引车(AGV)的实现是智能移动机器人研究的重要内容之一． 阐述了自动导引车系统(AGVS)的构
成及工作原理，在此基础上对试验型AGV 模型的功能结构与硬件配置进行了详细的设计，并从软件上得以实现．
通过测试，表明该AGV模型达到了预期效果，为工业应用AGVS的开发提供了参考．     

温湿度对蜂窝纸板静力学性能影响及有限元分析

目的 针对目前定制家具打包运输过程AGV避障方法中,对障碍物信息辨识度较低、难以做到精准避障等问题,提出一种采用视觉传感器基于改进目标检测算法的AGV避障策略。方法 利用Mobilenet模型改进传统SSD目标检测算法,以AGV工作环境数据对训练后的SSD-Mobilenet模型进行迁移学习,结合视觉、超声波等多个模块实现避障原理,搭建以树莓派3B+为控制核心的实验平台进行相关实验研究。结果 实验证明该方法的检测精度达到94%,能够精准辨别障碍物类型;目标检测避障方法的避障通过时间比传统方法减少了15.8%～27.3%。结论 该方法有效提高了AGV避障的准确率与效率,可广泛应用在AGV避障控制中。     

一种简便的超声波声时精密测量技术

本文介绍了一种用于测量超声波传播时间的新颖实时数字平均技术，它能用常规的超声脉冲回波方法直接测量给定的两个不同回波“过零电平周期”之间的时间间隔，其精度优于１．０ｎｓ（纳秒）。这一系统由简单，价廉的电子元件组成，不需要任何人工调节就可自动给出超声渡越时间，本文还给出了不同测试条件下的若干实验结果。     

磁带导引AGV的自抗扰循迹控制方法

本文研究了磁带导引自动导引小车(AGV)的循迹控制问题,设计了一种线性自抗扰控制器,以达到AGV精准循迹、抗干扰能力强的控制要求。首先,建立了磁带导引AGV循迹误差系统的数学模型,将循迹控制系统的不确定动态描述为系统的加性总和干扰,通过设计扩张状态观测器对这些干扰量进行实时估计,进一步,设计线性自抗扰控制器对这些干扰进行动态线性化补偿,从而降低AGV循迹模型的不确定性及循迹过程中外部随机干扰对循迹控制性能的影响。最后,搭建了磁带导引AGV实验平台,并在该平台上验证了所提出方法的有效性和优越性。     

全局视觉AGV开环控制转向原理的研究

论文介绍了全局视觉AGV开环转向控制原理,在确定的工作环境下,通过图像处理建立了基于全局视觉的虚拟坐标系。分析了视觉导航AGV在曲线跟踪时精度下降的原因,提出了在全局视觉模式下,用开环转向控制的方法实现AGV特定转弯角。样车系统在不同的转弯半径、地面摩擦及速度下验证了该方法的可行。     

考虑冲突避免的多AGV路径规划研究

目的 提高物流企业“货到人”拣选系统在实际生产中的工作效率，避免自动导引小车(AGV)间的冲突死锁，研究大规模多AGV的无冲突路径规划和协同避障问题。方法 首先考虑AGV空载、负载情况和路径扩展成本，改进A^*算法，动态调整代价函数，优化路径扩展方式。其次，提出冲突检测及避免算法，对可能产生局部冲突的路径交叉点进行避障调度，通过预约锁格，实现局部冲突的检测，制定优先级避障策略，解决AGV动态行驶路径上产生的局部冲突和死锁，进而实现全局无冲突路径规划。结果 对多组不同任务量和不同AGV规模的场景进行仿真，实验结果表明，考虑冲突避免的改进A^*算法能有效实现100个任务、90个货架单位和7个拣选站场景下的多AGV动态路径规划，相较于传统A^*算法，其平均拣选时长缩短了52.61%。结论 该方法可实现大规模场景下的多AGV动态路径规划，在付出较小转弯代价的同时有效避免局部动态冲突，该方法可为相关企业实现多AGV协同调度提供新的思路和理论依据。     

激光导引AGV的自动引导系统设计

 激光导引技术是目前AGV系统普遍采用的引导方法，柔性好和精确高是其突出特点．介绍了AGV的基本概念、导引方式、车体结构和运动控制方式，重点介绍了激光扫描车体方位计算原理并结合路径轨迹推算导向法，设计了激光导引AGV的自动引导系统的结构和软件功能。     

AGV混合导引系统的研究与实现

AGV混合导引系统结合了电磁导引与射频识别(Radio Frequency Identification,RFID),并使用3种不同的路径选择方法实现了系统的导航功能。该系统对AGV硬件电路及导航信号源进行了精密设计,同时实现了包括无线通信的软件控制系统及四级保护的安全开发系统。测试结果显示,系统的测量与控制信号具有较高的精度和稳定性,AGV混合导引系统解决了国内电磁导航技术不能适应复杂路径的局限性,在导航、定位和路径规划上实现了技术突破,提高了AGV的生产效率。     

AGV在电力系统中的应用

本文通过AGV这一自动化高科技产品在电力系统的应用,介绍了AGV的结构特点及工作流程。     

浅谈如何提升AGV小车的效率

AGV小车技术是当今汽车工业必不可少的技术,而三举升AGV小车的应用更使汽车发动机及后桥的装配效率得到大大的提高。本文以上汽通用五菱宝骏基地总装车间的AGV小车系统为例,讲述了在AGV控制原理基础上,通过各种改善,使AGV小车运行效率得到明显提升。     

基于IGPS和麦克纳姆轮的AGV导航控制系统设计

目前常规使用的舵轮和差速轮自动导引车（automated guided vehicle,AGV）的精度和灵活性低,无法满足在大型高端产品装配过程中精确定位和导航的要求。为了进一步提高AGV的导航精度和柔性,提出了一种基于IGPS （indoor global positioning system,室内全球定位系统）和麦克纳姆轮的AGV高精度导航控制系统。首先通过IGPS高精度定位和坐标计算获取IGPS接收器的位置坐标,其次采用车体中心提取算法和坐标转换矩阵实现接收器坐标位置到车体中心坐标的转换,最后通过对全向移动AGV的建模,采用模糊PI控制方法对AGV的路径偏差进行纠正,实现AGV的精确定位和循迹导航。利用Simulink对模糊PI控制和传统PI控制进行仿真分析,结果表明,相对于传统PI控制,模糊PI控制响应速度快,调整曲线更平滑。同时,在基于IGPS的AGV试验平台进行试验,采用激光跟踪仪对AGV重复定位位置进行测量,结果显示定位精度达到±0.2 mm。研究结果对提高AGV的高精度定位能力具有借鉴意义,也为后续可移动机器人加工模式的研究提供参考。     

Comparison of dynamic routeing techniques for automated guided vehicle system

An automated Guided Vehicle (AGV) System with a limited number of vehicles cannot perform all of the transportation requests on demand. When a capacitated AGV system is used, then it is possible for the material handling system to become the bottleneck. There are many factors that affect the efficiency of an AGV system including how vehicles are routed and schedules. This paper presents a new dynamic approach to AGV routing. Simulation is used to study the effectiveness of this approach.     

Scheduling of Automated Guided Vehicles in a Decision Making Hierarchy

Scheduling efforts made without considering the special limitations of the material handling system might lead to infeasible results. An analytical model is proposed, first, to incorporate the automated guided vehicle (AGV) system into the overall decision making hierarchy. A mathematical formulation is developed to include interaction between the AGV module and other modules in the system by considering the restrictions of the material handling system. A micro-opportunistic approach is then proposed to solve the AGV scheduling problem. Finally, the proposed method is compared with a number of dispatching rules.     

Performance evaluation of tandem and conventional AGV systems using generalized stochastic Petri nets

This paper investigates the different policies and concepts followed in the traffic management of automated guided vehicle (AGV) systems, and develops the controls for automatically eliminating potential vehicle conflicts in an AGV system. The planning of the AGV system is performed in such a way that there are no conflicts or deadlocks for the vehicles using stochastic Petri nets (SPNs). The major effort is devoted to determining the benefits of the tandem AGV control in comparison with the conventional AGV control method. SPNs have been used to model the different designs of flexible manufacturing systems (FMSs) and with different policies for the movement of material, vehicle path control, inventory planning and tool control. The SPN model is solved and the performance of the system can be evaluated. In this study, the effort is directed to model an FMS with two different types of AGV traffic management methods, namely the conventional and tandem AGV control. A SPN program is used which takes the FMS Petri net model as the input and evaluates the different properties of the Petri net. Finally the performance measures are obtained, which helps in evaluating and comparing the two different AGV traffic management methods.     

面向仓库货架的商品智能拣选机器人设计

目的 为降低仓储拣选作业的劳动强度、提高拣选准确率,设计一款可代替人工拣货的拣选机器人。方法 基于PaddlePaddle的PP-ShiTu图像识别系统,实现货架商品的精确识别和种类的快速更新;针对低成本机械臂的视觉抓取问题,提出基于“无标定3D视觉+AGV运动控制”的货架商品抓取引导方法;采用二维码自主导航和智能升降系统实现了货架商品的搬运和立体抓取。结果 实验证明,所设计的拣选机器人实现了货架商品的精确抓取和搬运,测试准确率达到了92.25%。结论 基于该方法构建的智能拣选机器人,可以完成仓库货架商品的拣选和搬运。     

面向“货到人”拣选系统的一种随机调度策略

通过“货到人”拣选系统作业流程分析,提出了在分批下发订单任务的情况下的一种随机调度策略。以AGV (automated guided vehicle)完成所有任务的总时间最短为目标函数,以任务分配为决策变量,考虑进行调度时AGV所处的状态以及在完成任务过程中AGV在拣选台的排队等待时间,建立随机调度策略的数学规划模型。利用遗传算法进行求解,通过实例仿真,验证了随机调度策略较调度空闲AGV策略具有更高的拣选效率,同时解决了AGV调度与拣选序列问题,对AGV数量配置具有指导作用。     

A hybrid modelling approach to the design of an AGV-based material handling system for an FMS

The problem of organizing and controlling the material handling activity in an AGV-based material handling system for a flexible manufacturing system involves several decisions such as the number of vehicles required for the system, the layout of the tracks, the dispatching rules for the vehicles and the provision of control zones and buffers. This paper demonstrates the use of a two-stage approach for solving the problem. The required number of vehicles is estimated using an analytical model in the first stage. In the next stage, the effects of AGV failures and AGV dispatching rules on the system performance are observed through simulation studies based on which the AGV dispatching rule can be chosen.     

A neural algorithm for finding the shortest flow path for an automated guided vehicle system

The automated guided vehicle (AGV)system is emerging as the dominant technology to maximize the flexibility of material handling, while increasing the overall productivity of manufacturing operations. This paper presents a new way of finding the shortest flow path for an AGV system on a specific routing structure. An optimal solution of the system is determined by using an approach based on the Hopfield neural network with the simulated annealing (SA) procedure. In other words, the proposed approach reduces the total cost of an AGV delivery path from one workstation to another on the shop floor. By changing the temperature of the two-stage SA, a solution can be found that avoids potential collisions between AGVs. Both the flow path and the potential collision, which are major problems in AGV systems, may be solved simultaneously by the proposed neural network approach. Other advantages offered by the proposed method are its simplicity compared with operations research (OR)methods and a decreased number of needed AGVs. The performance of the approach is also investigated.