Today a group of automated guided vehicles at Toyota Material Handling Manufacturing Sweden detect and avoid objects primarily by using 2D-LiDAR, with shortcomings being the limitation of only scanning the area in a 2D plane and missing objects close to the ground. Several dynamic obstacles exist in the environment of the vehicles. Protruding forks are one such obstacle, impossible to detect and avoid with the current choice of sensor and its placement. This thesis investigates possible solutions and limitations of using a single RGB camera for obstacle detection, tracking, and avoidance. The obstacle detection uses the deep learning model YOLOv5s. A solution for semi-automatic data gathering and labeling is designed, and pre-trained weights are chosen to minimize the amount of labeled data needed. Two different approaches are implemented for the tracking of the object. The YOLOv5s detection is the foundation of the first, where 2D-bounding boxes are used as measurements in an Extended Kalman Filter (EKF). Fiducial markers build up the second approach, used as measurements in another EKF. A state lattice motion planner is designed to find a feasible path around the detected obstacle. The chosen graph search algorithm is ARA*, designed to initially find a suboptimal path and improve it if time allows.  The detection works successfully with an average precision of 0.714. The filter using 2D-bounding boxes can not differentiate between a clockwise and counterclockwise rotation, but the performance is improved when a measurement of rotation is included. Using ARA* in the motion planner, the solution sufficiently avoids the obstacles.

In recent years, customers' life stylish and behaviour have been changed and their tendencies become more diverse than before. As well as, market researches show a growing trend of special demands in their inclination. Accordingly, the companies compete to meet market demands for the reason of satisfying and maintaining the loyalty of their customers. This has led researchers to seek flexible methods and optimum solutions in production processes. In this regard, the manufacturing flow is one of the places in which flexibility and optimization can cause improvement is the assembly line. So, to meet the increasing diversity of market demand, assembly line processes must have the flexibility and ability to dynamically change product specifications and features while minimizing the operating and production processes' costs. For this reason, companies use solutions for designing assembly lines based on designing a flexible manufacturing system (FMS) for fast and better managing material feeding and handling. The FMS is a manufacturing method that is developed to easily can compatible with changes in production in the type and quantity of the product that has been manufactured. The performance of an FMS depends on the precise and efficient scheduling of material handling equipment. In this regard, the use of automated guided vehicles (AGV) instead of conveyors in an assembly line provid effectiveness and transformative.The aim of this research is to obtain the optimal numbers of AGVs required for the purpose of material handling at assembly lines. To solve the problem, a mathematical model has been developed. The objective function of the model is the number of AGVs. Accordingly, a set of variables and constraints have been determined have been considered to solve the linear optimization equation. In addition, the influence of workstations’ buffer capacity on material handling activities and the number of AGVs are studied by using this developed mathematical model.In order to evaluate experiments and analysis of the problem, Python programming software and its libraries have been used to calculate rapidly and accurately equations of the model. Preliminary results show that according to the layout of the production line and demand/production planning, as well as determining the size of input and output buffers of workstations, the proposed mathematical model calculates the minimum number of required vehicles and by changing the size of buffers we achieve different results. The aforementioned IT artefact is implemented in the direction of industrial digitalization and can be developed as application software in the eventuality. And further, this master project is desirable to take performance to continue sustainable development principles. / <p>Examensarbetet är på 16,5 hp:</p><p>Master Degree Project in Virtual Product RealizationOne year Level 16.5 ECTSSpring term 2022</p>

Rapporten är en förstudie som kan använda av Batterifabrik AB när de tar beslut om de ska implementera AGV i deras produktion. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

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A Flexible Manufacturing System (FMS) is an integrated system consisting of several automated work centers interconnected by an automated material handling system. An integrated scheduling methodology is required to schedule all FMS sub-systems. The overall objective of this research was to develop a scheduling methodology to integrate job sequencing and Automatic Guided Vehicle System dispatching within a FMS environment. To develop the new scheduling methodology, the currently used AGVS controller decision set was examined and expanded. The expanded decision set gives the AGVS controller more options to choose from when scheduling the AGVS. The developed integrated scheduling methodology contains four steps. The first step determines which job is to be processed next by each work center based on job sequencing heuristics. The second step determines which work center is to be serviced next by the AGVS based on the estimated time till the work center is forced to stop production. The third step determines which specific job is to be serviced next by the AGVS by combining the work centers' processing orders and the work center servicing priorities. The fourth step decides which AGV is to transport the job requiring immediate service. Based on the preliminary study of a fictitious FMS, the new scheduling methodology showed a statistically significant increase in total job throughput, and a significant decrease in average flow time. Work center utilization also increased. A slight increase in unloaded AGV travel time was found, but was outweighed by the other benefits. / Master of Science

The purpose of this research was to develop and validate a simulation framework for automated guided vehicle systems (AGVSs). The framework that was developed, AGVSF, uses the discrete, next-event simulation method and the C programming language. AGVSF consists of an organizational structure that provides for control of the execution of the simulation and a set of modular C functions used to model the AGVS. The structure of AGVSF allows the user to organize the Simulation logic in a consistent manner. The modularity and flexibility of the code result from clearly defining the interdependencies of the functions that make up the various events and operations of the simulation. This enables the user to substitute functions where needed to represent new operational methods which are not directly provided in the original framework code set. A set of functions is provided within AGVSF for modeling basic AGVSs and AGVS layouts. The framework concept has been validated by simulating an AGVS under different operating conditions and control algorithms. / Master of Science

Container Terminals are experiencing increased pressure to raise their productivity levels and capacity, in order to handle the increasing amounts of container cargo due to globalization. Due to space restrictions and other financial factors, automated solutions have been developed. AGVs (Automated Guided Vehicles) are one of those automated solutions for the horizontal transportation with in a Container Terminal. A recent European sponsored project has lead to the development of a new generation of AGVs that are using cassettes namely IPSI™ AGVs. An agent-based simulator has been developed with the purpose of constructing and evaluating dispatching strategies for this new developed AGV system. Already explored dispatching strategies [9, 14] are used with additional modifications to re-evaluate them with the consideration of the usage of cassettes. Our findings from the simulation experiment are suggesting that a cost estimation based approach is much more suited than an inventory based. In addition to that, the results are very convincing in that the number of cassettes used is the most dominate factor despite dispatching strategy for obtaining a fast ship turnaround time.

This master thesis deals with design of the automated guided vehicle (AGV) for securing of material flow in industry. Emphasis is placed especially on the locomotion system, which includes steering mechanism, traction propulsion with gearbox and traction batteries. This thesis also includes design of the vehicle’s frame and its strength check using finite element method. Part of this thesis is also production drawings of the selected parts and total drawing set of the AGV.

This research identifies the attributes to be considered in the selection of an automated guided vehicle (AGV). A distinction is made between automated guided vehicles (AGVs) and an automated guided vehicle system (AGVS). This research is concerned only with the selection of automated guided vehicles (AGVs). A selection model is developed which forces the user to evaluate attributes. his requirements and preferences for AGV The first step of the model allows the user to enter his specifications for AGV attributes which are applicable to his production environment. The second step in the selection model is for the user to determine 8-15 attributes to use as selection criteria. In the third phase, the user inputs his preferences and priorities with respect to the attributes chosen as selection criteria in the second step. model ranks the Based on this information, the selection AGV models in the feasible set. A description of the model and a numerical example are included. Steps 1 and 2, described above, are implemented using an R:BASE™ program. The BASIC computer language was used to perform the interrogation of the user with respect to his priorities and preferences among attributes in Step 3. The IBM PC™ is the hardware chosen for running the selection model. / M.S.

Thesis (M. Tech. (Engineering: Electrical)) -- Central University of technology, Free State, 2013 / Automatic Guided Vehicles (AGVs) are being used more frequently in a manufacturing environment. These AGVs are navigated in many different ways, utilising multiple types of sensors for detecting the environment like distance, obstacles, and a set route. Different algorithms or methods are then used to utilise this environmental information for navigation purposes applied onto the AGV for control purposes. Developing a platform that could be easily reconfigured in alternative route applications utilising vision was one of the aims of the research. In this research such sensors detecting the environment was replaced and/or minimised by the use of a single, omnidirectional Webcam picture stream utilising an own developed mirror and Perspex tube setup. The area of interest in each frame was extracted saving on computational recourses and time. By utilising image processing, the vehicle was navigated on a predetermined route. Different edge detection methods and segmentation methods were investigated on this vision signal for route and sign navigation. Prewitt edge detection was eventually implemented, Hough transfers used for border detection and Kalman filtering for minimising border detected noise for staying on the navigated route. Reconfigurability was added to the route layout by coloured signs incorporated in the navigation process. The result was the manipulation of a number of AGV’s, each on its own designated coloured signed route. This route could be reconfigured by the operator with no programming alteration or intervention. The YCbCr colour space signal was implemented in detecting specific control signs for alternative colour route navigation. The result was used generating commands to control the AGV through serial commands sent on a laptop’s Universal Serial Bus (USB) port with a PIC microcontroller interface board controlling the motors by means of pulse width modulation (PWM). A total MATLAB® software development platform was utilised by implementing written M-files, Simulink® models, masked function blocks and .mat files for sourcing the workspace variables and generating executable files. This continuous development system lends itself to speedy evaluation and implementation of image processing options on the AGV. All the work done in the thesis was validated by simulations using actual data and by physical experimentation.