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的顯著特點是無人駕駛，I-SO AGV上裝備有自動導向系統，可以保障系統在不需要人工引航的情況下就能夠沿預定的路線自動行駛，將貨物或物料自動從起始點運送到目的地。I-SO AGV的另一個特點是柔性好，自動化程度高和智能化水平高，I-SO AGV的行駛路徑可以根據倉儲貨位要求、生產工藝流程等改變而靈活改變，并且運行路徑改變的費用與傳統的輸送帶和剛性的傳送線相比非常低廉。I-SO AGV一般配備有裝卸機構，可以與其他物流設備自動接口，實現貨物和物料裝卸與搬運全過程自動化。此外，I-SO AGV還具有清潔生產的特點，I-SO AGV依靠自帶的蓄電池提供動力，運行過程中無噪聲、無污染，可以應用在許多要求工作環境清潔的場所。
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.
1). I-SO電磁感應引導式AGV （由于這種技術相對落后和性能缺陷，一般環境下I-SO智能 AGV很少采用）
2). I-SO激光引導式AGV （適合高附加值，高環境要求行業生產制造使用）
I-SO視覺引導式AGV 是我們正在快速發展和成熟的AGV，該AGV上裝有CCD攝像機和傳感器，在車載計算機中設置有AGV欲行駛路徑周圍環境圖像數據庫。AGV行駛過程中攝像機動態獲取車輛周圍環境圖像信息并與圖像數據庫進行比較，從而確定當前位置并對下一步行駛做出決策。 這種AGV由于不要求人為設置任何物理路徑，因此在理論上具有最佳的引導柔性，隨著計算機圖像采集、儲存和處理技術的飛速發展，能夠識別物品和行人（如盤子.碗.顧客）該種AGV的實用性越來越強。
4).I-SO磁帶導引AGV (通用型，適合所有行業使用)I-SO磁帶導引AGV 在工作區間地板上鋪設磁帶，AGV通過磁場傳感器檢測磁帶信號控制走行，這種技術目前成本最低，施工簡單可快速更改路徑，不受環境影響可靠性高，可滿足大部分行業要求，I-SO磁帶導引AGV 在站點設置上突破了傳統技術自主開發了AGV專用RFID隱藏式站標和讀寫器，讓行駛線路設置更加柔性?！ ?br/>此外，還有鐵磁陀螺慣性引導式AGV、光學引導式AGV等多種形式的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.
2. AGV Applications
(3) Post offices, libraries, port terminals and airports;
(4) Tobacco, medicine, food, chemical industry;
(5) Hazardous Locations and Specialty Industries.
1． 數學規劃方法 ：為AGV選擇最佳的任務及最佳路徑，可以歸納為一個任務調度問題。數學規劃方法是求解調度問題最優解的傳統方法，該方法的求解過程實際上是一個資源限制下的尋優過程。實用中的方法主要有整數規劃、動態規劃、petri方法等。在小規模調度情況下，這類方法可以得到較好的結果，但是隨著調度規模的增加，求解問題耗費的時間呈指數增長，限制了該方法在負責、大規模實時路線優化和調度中應用。
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.