不论是普通制造业还是码头仓库，物料装卸和搬运都是物流的要素之一，在物流系统中成本占比也很高。美国工业生产过程中装卸搬运费用占成本的20~30%，德国物流企业物料搬运费用占营业额的35%，日本物流搬运费用占10%，我国生产物流中装卸搬运费用约占加工成本的20%，所以企业一直都在最完美的自动化智能化的搬运技术和装备。AGV机器人一种柔性化和智能化物流搬运机器人，在国外从50年代在仓储业开始使用，目前已经在制造业、港口、码头等领域得到普遍应用，在国内逐渐也有部分企业重视并应用AGV来完成一些简单的搬运任务。下面我们就来简单分析I-SO智能AGV机器人与现代智能化物流应用。
Regardless of whether it is a general manufacturing industry or a dock warehouse, material handling and handling are one of the elements of logistics, and the cost ratio in the logistics system is also high. In the process of industrial production in the United States, loading, unloading and handling costs account for 20-30% of the cost, German logistics companies’ material handling costs account for 35% of the turnover, and Japan’s logistics and handling costs account for 10%. In my country’s production logistics, loading, unloading and handling costs account for about 20% of the processing cost. %, so the company has always been in the most perfect automation and intelligent handling technology and equipment. AGV robot is a flexible and intelligent logistics handling robot. It has been used in the warehousing industry in foreign countries since the 1950s. It has been widely used in manufacturing, ports, docks and other fields. In China, some enterprises have gradually attached importance to and applied AGV to Complete some simple carrying tasks. Let's briefly analyze the I-SO intelligent AGV robot and the application of modern intelligent logistics.
Analysis of Intelligent AGV Robot and Modern Intelligent Logistics Application
I-SO AGV的显著特点是无人驾驶，I-SO AGV上装备有自动导向系统，可以保障系统在不需要人工引航的情况下就能够沿预定的路线自动行驶，将货物或物料自动从起始点运送到目的地。I-SO AGV的另一个特点是柔性好，自动化程度高和智能化水平高，I-SO AGV的行驶路径可以根据仓储货位要求、生产工艺流程等改变而灵活改变，并且运行路径改变的费用与传统的输送带和刚性的传送线相比非常低廉。I-SO AGV一般配备有装卸机构，可以与其他物流设备自动接口，实现货物和物料装卸与搬运全过程自动化。此外，I-SO AGV还具有清洁生产的特点，I-SO AGV依靠自带的蓄电池提供动力，运行过程中无噪声、无污染，可以应用在许多要求工作环境清洁的场所。
The distinctive feature of I-SO AGV is that it is unmanned. The I-SO AGV is equipped with an automatic guidance system, which can ensure that the system can automatically drive along the predetermined route without manual piloting, and automatically start the goods or materials from the starting point. Shipping from origin to destination. Another feature of I-SO AGV is good flexibility, high degree of automation and high level of intelligence. The driving path of I-SO AGV can be flexibly changed according to changes in storage space requirements, production process flow, etc., and the cost of changing the operating path Very inexpensive compared to traditional conveyor belts and rigid conveyor lines. I-SO AGV is generally equipped with a loading and unloading mechanism, which can automatically interface with other logistics equipment to realize the automation of the whole process of loading, unloading and handling of goods and materials. In addition, I-SO AGV also has the characteristics of clean production. I-SO AGV relies on its own battery to provide power. It is noise-free and pollution-free during operation, and can be used in many places that require a clean working environment.
I-SO智能 AGV的种类
AGV从发明至今已经有50年的历史，随着应用领域的扩展，其种类和形式变得多种多样。我们根据I-SO AGV自动行驶过程中的导航方式将AGV分为以下几种类型：
1). I-SO电磁感应引导式AGV （由于这种技术相对落后和性能缺陷，一般环境下I-SO智能 AGV很少采用）
电磁感应式引导一般是在地面上，沿预先设定的行驶路径埋设电线，当高频电流流经导线时，导线周围产生电磁场，AGV上左右对称安装有两个电磁感应器，它们所接收的电磁信号的强度差异可以反映AGV偏离路径的程度。AGV的自动控制系统根据这种偏差来控制车辆的转向，连续的动态闭环控制能够保证AGV对设定路径的稳定自动运行。由于这种电磁感应引导式导航方法才安装施工比较繁杂无法随时更新AGV行驶路径，同时容易受到电磁环境干扰，目前部分国内AGV制造厂商仍在商业化的AGV上使用，尤其是适用于大中型的AGV。
2). I-SO激光引导式AGV （适合高附加值，高环境要求行业生产制造使用）
I-SO激光引导式AGV上安装有可旋转的激光扫描器，在运行路径沿途的墙壁或支柱上安装有高反光性的定位标志，AGV依靠激光扫描器发射激光束，然后接受由四周定位标志反射回的激光束，车载计算机计算出车辆当前的位置以及运动的方向，通过和内置的数字地图进行对比来校正方位，从而实现自动搬运。
目前I-SO激光引导式AGV的应用范围普遍，并且依据同样的引导原理，若将激光扫描器更换为红外发射器或超声波发射器，则激光引导式AGV可以变为红外引导式AGV和超声波引导式AGV。 I-SO激光引导式AGV成本较高，在普通制造业较少推荐，适合生化制药，烟草，芯片等高附加值行业使用。
3). I-SO视觉引导式AGV
I-SO视觉引导式AGV 是我们正在快速发展和成熟的AGV，该AGV上装有CCD摄像机和传感器，在车载计算机中设置有AGV欲行驶路径周围环境图像数据库。AGV行驶过程中摄像机动态获取车辆周围环境图像信息并与图像数据库进行比较，从而确定当前位置并对下一步行驶做出决策。 这种AGV由于不要求人为设置任何物理路径，因此在理论上具有最佳的引导柔性，随着计算机图像采集、储存和处理技术的飞速发展，能够识别物品和行人（如盘子.碗.顾客）该种AGV的实用性越来越强。
4).I-SO磁带导引AGV (通用型，适合所有行业使用)I-SO磁带导引AGV 在工作区间地板上铺设磁带，AGV通过磁场传感器检测磁带信号控制走行，这种技术目前成本最低，施工简单可快速更改路径，不受环境影响可靠性高，可满足大部分行业要求，I-SO磁带导引AGV 在站点设置上突破了传统技术自主开发了AGV专用RFID隐藏式站标和读写器，让行驶线路设置更加柔性。
此外，还有铁磁陀螺惯性引导式AGV、光学引导式AGV等多种形式的AGV。
Types of I-SO Intelligent AGV
AGV has a history of 50 years since its invention. With the expansion of application fields, its types and forms have become diverse. We divide AGVs into the following types according to the way of navigation during the automatic driving of I-SO AGVs:
1. I-SO electromagnetic induction guided AGV (due to the relatively backward technology and performance defects of this technology, I-SO intelligent AGV is rarely used in general environment)
Electromagnetic induction guidance is generally on the ground, and wires are buried along a preset driving path. When high-frequency current flows through the wires, an electromagnetic field is generated around the wires. Two electromagnetic sensors are installed symmetrically on the AGV. The difference in the strength of the electromagnetic signal can reflect the degree to which the AGV deviates from the path. The automatic control system of the AGV controls the steering of the vehicle according to this deviation, and the continuous dynamic closed-loop control can ensure the stable and automatic operation of the AGV on the set path. Due to the complicated installation and construction of this electromagnetic induction-guided navigation method, the AGV driving path cannot be updated at any time, and it is easily interfered by the electromagnetic environment. At present, some domestic AGV manufacturers are still using it on commercial AGVs, especially for large and medium-sized AGVs. AGV.
2. I-SO laser-guided AGV (suitable for high value-added, high environmental requirements industries production and use)
A rotatable laser scanner is installed on the I-SO laser-guided AGV, and highly reflective positioning marks are installed on the walls or pillars along the running path. The AGV relies on the laser scanner to emit a laser beam, and then receives the surrounding positioning marks. With the reflected laser beam, the on-board computer calculates the current position and direction of movement of the vehicle, and corrects the orientation by comparing it with the built-in digital map, thereby realizing automatic handling.
At present, the application range of I-SO laser-guided AGV is widespread, and according to the same guiding principle, if the laser scanner is replaced with an infrared transmitter or an ultrasonic transmitter, the laser-guided AGV can become an infrared-guided AGV and an ultrasonic-guided AGV. type AGV. The cost of I-SO laser-guided AGV is relatively high, and it is less recommended in ordinary manufacturing industries. It is suitable for use in high value-added industries such as biochemical pharmaceuticals, tobacco, and chips.
3. I-SO vision-guided AGV
The I-SO vision-guided AGV is our rapidly developing and mature AGV. The AGV is equipped with CCD cameras and sensors, and the on-board computer is provided with an image database of the surrounding environment of the AGV's desired path. During the driving process of the AGV, the camera dynamically obtains the image information of the surrounding environment of the vehicle and compares it with the image database, so as to determine the current position and make a decision on the next driving. Since this AGV does not require any physical path to be set manually, it has the best guiding flexibility in theory. With the rapid development of computer image acquisition, storage and processing technology, it can identify items and pedestrians (such as plates, bowls, customers) The practicability of this kind of AGV is getting stronger and stronger.
4. I-SO tape-guided AGV (universal, suitable for all industries)
I-SO tape-guided AGV lays tape on the floor of the work area, and the AGV controls the running by detecting the tape signal through the magnetic field sensor. This technology is currently the lowest cost , The construction is simple, the path can be changed quickly, and it is not affected by the environment. Writer to make the driving route setting more flexible.
In addition, there are various forms of AGV such as ferromagnetic gyro inertial-guided AGV and optically-guided AGV.
AGV Path Design Drawing
二 AGV的应用
1．仓储业；
2．制造业；
3．邮局、图书馆、港口码头和机场；
4．烟草、医药、食品、化工；
5．危险场所和特种行业。
2. AGV Applications
(1) Warehousing;
(2) Manufacturing;
(3) Post offices, libraries, port terminals and airports;
(4) Tobacco, medicine, food, chemical industry;
(5) Hazardous Locations and Specialty Industries.
I-SO智能 AGV使用中的路线优化和实时调度的方法和研发方向：
1． 数学规划方法 ：为AGV选择最佳的任务及最佳路径，可以归纳为一个任务调度问题。数学规划方法是求解调度问题最优解的传统方法，该方法的求解过程实际上是一个资源限制下的寻优过程。实用中的方法主要有整数规划、动态规划、petri方法等。在小规模调度情况下，这类方法可以得到较好的结果，但是随着调度规模的增加，求解问题耗费的时间呈指数增长，限制了该方法在负责、大规模实时路线优化和调度中应用。
2． 仿真方法：仿真方法通过对实际的调度环境建模，从而对AGV的一种调度方案的实施进行计算机的模拟仿真。我们使用仿真手段对某些调度方案进行测试、比较、监控，从而改变和挑选调度策略。实用中采用的方法有离散事件仿真方法、面向对象的仿真方法和3维仿真技术，有许多软件可以用于AGV的调度仿真，其中Witness软件可以快速建立仿真模型，实现仿真过程三维演示和结果的分析处理。
3． 人工智能方法：人工智能方法把AGV的调度过程描述成一个在满足约束的解集搜索最优解的过程。它利用知识表示技术将人的知识包括进去，同时使用各种搜索技术力求给出一个令人满意的解。具体的方法有专家系统方法、遗传算法、启发式算法、神经网络算法。其中专家系统方法在实用中较多采用，它将调度专家的经验抽象成系统可以理解和执行的调度规则，并且采用冲突消解技术来解决大规模AGV调度中的规则膨胀和冲突问题。
由于神经网络具有并行运算、知识分布存储、自适应性强等优点，因此，它成为求解大规模AGV调度问题是一个很有希望的方法。目前，用神经网络方法成功的求解了TSP-NP问题，求解中，神经网络能把组合优化问题的解转换成一种离散动力学系统的能量函数，通过使能量函数达到最小而求得优化问题的解。
遗传算法是模拟自然界生物进化过程中的遗传和变异而形成的一种优化求解方法。遗传算法在求解AGV的优化调度问题时，首先通过编码将一定数量的可能调度方案表示成适当的染色体，并计算每个染色体的适应度（如运行路径最短），通过重复进行复制、交叉、变异寻找适应度大的染色体，即AGV调度问题的最优解。
单独用一种方法来求解调度问题，往往存在一定的缺陷。目前，将多种方法进行融合来求解AGV的调度问题是一个研究热点。如，将专家系统和遗传算法融合，把专家的知识融入到初始染色体群的形成中，以加快求解速度和质量。
The method and research and development direction of route optimization and real-time scheduling in the use of I-SO intelligent AGV:
1. Mathematical programming method: Selecting the best task and the best path for AGV can be summarized as a task scheduling problem. Mathematical programming method is a traditional method to solve the optimal solution of scheduling problem. The solution process of this method is actually an optimization process under resource constraints. Practical methods mainly include integer programming, dynamic programming, and petri methods. In the case of small-scale scheduling, this kind of method can get better results, but with the increase of the scheduling scale, the time spent to solve the problem increases exponentially, which limits the application of this method in responsible, large-scale real-time route optimization and scheduling .
2. Simulation method: The simulation method simulates the implementation of a scheduling scheme of AGV by modeling the actual scheduling environment. We use simulation to test, compare, and monitor certain scheduling schemes to change and choose scheduling strategies. The methods used in practice include discrete event simulation method, object-oriented simulation method and 3D simulation technology. There are many softwares that can be used for AGV scheduling simulation. Among them, Witness software can quickly establish simulation model and realize 3D demonstration of simulation process and results. Analytical processing.
3. Artificial intelligence method: The artificial intelligence method describes the scheduling process of AGV as a process of searching for the optimal solution in the solution set that satisfies the constraints. It uses knowledge representation techniques to include human knowledge, and uses various search techniques to try to give a satisfactory solution. Specific methods include expert system method, genetic algorithm, heuristic algorithm, neural network algorithm. Among them, the expert system method is mostly used in practice. It abstracts the experience of scheduling experts into scheduling rules that the system can understand and execute, and uses conflict resolution technology to solve the problem of rule expansion and conflict in large-scale AGV scheduling.
Because the neural network has the advantages of parallel operation, knowledge distribution and storage, and strong adaptability, it is a promising method for solving large-scale AGV scheduling problems. At present, the TSP-NP problem has been successfully solved by the neural network method. During the solution, the neural network can convert the solution of the combinatorial optimization problem into an energy function of a discrete dynamic system, and obtain the optimization problem by minimizing the energy function. untie.
Genetic algorithm is an optimization solution method formed by simulating the heredity and variation in the process of biological evolution in nature. When the genetic algorithm solves the optimal scheduling problem of AGV, it first expresses a certain number of possible scheduling schemes into appropriate chromosomes through coding, and calculates the fitness of each chromosome (such as the shortest running path), and repeats, crosses, and mutates through repetition. Find the chromosome with large fitness, that is, the optimal solution of the AGV scheduling problem.
Using a single method to solve the scheduling problem often has certain defects. At present, it is a research hotspot to integrate multiple methods to solve the AGV scheduling problem. For example, the expert system and genetic algorithm are integrated, and the knowledge of experts is integrated into the formation of the initial chromosome group to speed up the solution speed and quality.
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