Design and implementation of agv commodities transportation

MINISTRY OF EDUCATION AND TRAINING HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION FACULTY FOR HIGH QUALITY TRAINING GRADUATION THESIS ELECTRONICS AND COMMUNICATIONS ENGINEERING TECHNOLOGY DESIGN AND IMPLEMENTATION OF AGV COMMODITIES TRANSPORTATION ADVISOR : ASSOC.PROF TRUONG NGOC STUDENTS : SONTRUONG THI BICH CHI QUACH THAI LONG SKL010821 Ho Chi Minh City, July 2023 HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION FACULTY FOR HIGH-QUALITY TRAINING CAPSTONE DESIGN PROJECT DESIGN AND IMPLEMENTATION OF AGV COMMODITIES TRANSPORTATION Students: TRUONG THI BICH CHI ID Student: 19161044 QUACH THAI LONG ID student: 18161023 MAJOR : ELECTRONICS AND COMMUNICATIONS ENGINEERING TECHNOLOGY Advisor: Assoc.Prof TRUONG NGOC SON Ho Chi Minh City,07 /2023 THE SOCIALIST REPUBLIC OF VIETNAM Independence – Freedom– Happiness -Ho Chi Minh City ,July , 2023 PROJECT ASSIGNMENT Student name: Trương Thị Bích Chi Student ID: 19161044 Student name: Quách Thái Long Student ID: 18161023 Major: Electronics and Communication Engineering Technology Advisor: Assoc Prof Trương Ngọc Sơn Class: 19161CLA2, 18161CLA2 Phone number: 0931085929 Date of assignment: _ Date of submission: _ Project title: Design and implementation of AGV Commodities Transportation Initial materials provided by the advisor: _ Content of the project: _ Final product: CHAIR OF THE PROGRAM ADVISOR (Sign with full name) (Sign with full name) i THE SOCIALIST REPUBLIC OF VIETNAM Independence – Freedom– Happiness Ho Chi Minh City, July 7, 2023 ADVISOR’S EVALUATION SHEET Student name: Trương Thị Bích Chi Student ID: 19161044 Student name: Quách Thái Long Student ID: 18161023 Major: Electronics and Communication Engineering Technology Project title: Design and implementation of AGV commodities transportation Advisor: Assoc Prof Trương Ngọc Sơn EVALUATION Content of the project: Strengths: Weaknesses: Approval for oral defense? (Approved or denied) Overall evaluation: (Excellent, Good, Fair, Poor) Mark…………………… (in words………………………… ) Ho Chi Minh City, July 7, 2023 ADVISOR ii THE SOCIALIST REPUBLIC OF VIETNAM Independence – Freedom– Happiness Ho Chi Minh City, July 7, 2023 PRE-DEFENSE EVALUATION SHEET Student name: Student ID: Student name: Student ID: Major: Project title: Name of Reviewer: EVALUATION Content and workload of the project Strengths: Weaknesses: Approval for oral defense? (Approved or denied) Overall evaluation: (Excellent, Good, Fair, Poor) Mark:…………….(in words: ) Ho Chi Minh City,July 7, 2023 REVIEWER (Sign with full name) iii THE SOCIALIST REPUBLIC OF VIETNAM Independence – Freedom– Happiness Ho Chi Minh City, July 7, 2023 EVALUATION SHEET OF DEFENSE COMMITTEE MEMBER Student name: Student ID: Student name: Student ID: Major: Project title: Name of Reviewer: EVALUATION Content and workload of the project Strengths: Weaknesses: Approval for oral defense? (Approved or denied) Overall evaluation: (Excellent, Good, Fair, Poor) Mark:………….(in words: ) Ho Chi Minh City, July 7, 2023 REVIEWER (Sign with full name) iv DISCLAIMER Project implementation group states that this is the final report for Capstone Design Project, "Design and implementation of AGV commodities transportation" The simulations and study findings are accurate and were carried out entirely under the direction of the instructor, Assoc Prof TRUONG NGOC SON The report does not duplicate any other sources either Additionally, the paper includes a variety of cited and carefully labeled reference materials Before the department, faculty, and school, Project implementation group would like to fully accept responsibility for this promise Student TRUONG THI BICH CHI QUACH THAI LONG v ACKNOWLEDGEMENT To complete this Capstone Design Project, first of all, Project implementation group would like to express our sincere thanks to all the teachers in the Department of Electronic and communication Engineering Technology who have enthusiastically guided and equipped us with the necessary knowledge useful in the past semesters Project implementation group would like to express our deep gratitude to Assoc Prof Truong Ngoc Son, who directly guided and created all conditions to help us during the process of Capstone Design Project Due to the short implementation time of the project, limited knowledge, limitations and errors in the topic have not been completely overcome Project implementation group looks forward to receiving guidance and suggestions from you Project implementation group sincerely thank you! Student TRUONG THI BICH CHI QUACH THAI LONG vi CONTENTS LIST OF FIGURES ix LIST OF TABLES xi LIST OF ABBREVIATIONS xii CHAPTER 1.1 INTRODUCTION OVERVIEW 1.1.1 THE PROBLEM 1.1.2 REGARDING RATIONALE OF THE PROJECT 1.2 RESEARCH MISSION 1.3 OBJECT AND SCOPE OF THE PROJECT 1.3.1 OBJECT 1.3.2 SCOPE 1.4 RESEARCH METHODS 1.5 THE PROJECT’S CONTENT 1.6 STRUCTURE OF THE PROJECT CHAPTER 2.1 LITERATURE REVIEW SOFTWARE 2.1.1 OVERVIEW OF THE LIBRARY OPEN CV 2.2 QR CODE 2.3 ALGORITHM 2.3.1 GAUSSIAN IMAGE PROCESSING 2.3.2 CONVERT RGB TO HSV 2.3.3 CANNY 10 2.3.4 HOUGH TRANSFORM 12 2.3.5 APPLYING PD CONTROL 15 vii 2.3.6 2.4 CALCULATE THE ARM ROBOT 17 HARDWARE 18 2.4.1 OVERVIEW OF RASPBERRY PI 18 2.4.2 ARDUINO UNO R3 19 2.4.3 L298N 22 2.4.4 CAMERA 22 2.4.5 MG996R 23 2.4.6 POWER SUPPLY 26 CHAPTER DESIGN OF THE SYSTEM 28 3.1 REQUIREMENTS OF THE SYSTEM 28 3.2 HARDWARE CALCULATION AND DESIGN 28 3.2.1 Input Block 29 3.2.2 Central Processing Block 30 3.2.3 Executive Block 32 3.2.4 Power supply 33 3.3 The Schematic of system 34 3.4 SOFTWARE DESIGN 35 CHAPTER EXPERIMENT AND DISCUSSION 43 4.1 The results of system 43 4.2 System evaluation 50 CHAPTER CONCLUSION AND FUTURE WORK 53 5.1 CONCLUSIONS 53 5.2 FUTURE WORK 53 REFERENCES 54 viii selected object, the MCU will output the control pulse to the servo motors and the arm to its job, after that it will return to the default state 42 CHAPTER EXPERIMENT AND DISCUSSION 4.1 The results of system The general process of the system consists of three main parts: the user will use QR Code to determine the position given commodity including some QR Code differences represented to the warehouses After being scanned, the system camera will decode QR Code, after that the system car will detect lane and movement In the movement, the system car will be scanned on the road to identify the input QR Code the same as the QR Code scanned on the road Identify the position given commodity, the system arm robot will pick up the commodity and go to the position to initialize Figure 4.1 The result of the system Following Figure 4.1, when the vehicle scans QR Code through the camera marked When it receives the frame figure from the QR Code input, the arm robot will be notified to pick up the area purchasing as shown in figure 4.2 43 Figure 4.2 The result of arm robot pick up goods The camera begins to scan the QR code mounted on the vehicles After that, the system receives a signal from the arm robot, and the vehicle begins to detect lanes Case : The vehicle runs forward as shown on the figure 4.3 and figure 4.4 When the vehicle runs at an established angle of 90 degrees when working with PID to modify the vehicle to run in the lane without deviation Figure 4.3 The result of the system detect lane forward 44 Figure 4.4 The model experiment of detect lane forward Case : The vehicle runs turn left as shown on the figure 4.5 and figure 4.6 The angle will be less than 90 degrees when the tracking vehicle turns to the left Because the camera angle is limited, only one side of the left lane can be recognized when the vehicle turns left 45 Figure 4.5 The result of the system detect lane turn left Figure 4.6 The model experiment of detect lane turn left 46 Case 3: The vehicle runs turn right as shown on the figure 4.7 and figure 4.8 The angle will be bigger than 90 degrees when the tracking vehicle turns to the right Because the camera angle is limited, only one side of the right lane can be recognized when the vehicle turns left Figure 4.7 The result of the system detect lane turn right Figure 4.8 The model experiment of detect lane turn right 47 Every color will be represented by a different QR code, such as "Box2" being red and "Box3" being blue After the camera receives input QR Code , the vehicle detects the lane it uses the color of the road to calculate the warehouse's position If the color is detected simultaneously with a QR Code input, the vehicle will stop and drop down the purchase as shown in Figure 4.9 and figure 4.10 Figure 4.9 The model experiment of stop warehouse 48 Figure 4.10 The model experiment of stop warehouse The project implementation group uses methods to detect color to determine the vehicle's initial position In this case, the project implementation group uses the color white to determine the original return as shown in the figure 4.11 49 Figure 4.11 The model experiment of determine original position 4.2 System evaluation In general, the system operates smoothly and stably Table 4.1 summarizes the recognition results of the system such as turn left , go straight, detect QR, pick up the box, drop the box down, stop On the other hand, the time the camera scans the QR code is fast in normal environments that are being sent in as input images and frames from the camera during testing the system The table lists out the test results of the system, including cases, number of correct attempts, number of incorrect attempts and accuracy The overall efficiency of recognition QR is found to be exactly 100% The results are greatly affected by the QR Code, which are selected by users If the QR Code is more carefully selected, there will have an increase in the recognition That parallel, the time to detect original position and stop line, project implementation group use to detect color convert RGB to HSV After testing many times, the general efficiency of detecting and 50 classification of colors is found to be around 82% The results are stably by the stop and determine original position Table 4.1 Performance results of the system Case Number of correct Number of attempts incorrect attempts Turn left 57 43 57% Go straight 90 10 90% Detect QR 100 100% Pick up the box 65 35 65% Drop the box down 82 18 82% Stop 82 18 82% Average of Accuracy Accuracy 79.3% Specifically, the detect lane is based on two goals: turn left and proceed straight The detect turn left results are roughly 57% Project implementation group can see from the results of the experiment that the results are unstable, thus it is essential for two reasons The system's two characteristics are assessed: The mass and brightness of the vehicle The weight of the car will drastically affect the DC motor's performance If the project implementation group notices throughout the experiment that the vehicle without arm robot then the vehicle detects the lane with exactly 73% accuracy, as shown in table 4.2 However, when the vehicle is equipped with an arm the accuracy only accounts for 30% , so changing the vehicle’s mass effect to the detect speed when turning left decreases, causing the motor to stop or operate at a low speed So, the project implementation team decides that changing the motor to make the wheels active is sufficient When doing image processing, strong light is required because low light would result in noise The car will not be able to detect Table 4.2 Performance results when the vehicle detect lane without and with arm robot Case Number of correct Number of incorrect attempts attempts 51 Accuracy Without arm robot 73 27 73% With arm robot 30 70 30% Finally, the arm robot as shown in table 4.1 the rate pick up box is found to be around 82% The arm robot is largely responsible for 82% of the exact results by dropping the package The outcomes of the arm robot dropping the box depend on the stop line since the robot will precisely lower the box when the vehicle stops in the warehouse's specific location 52 CHAPTER CONCLUSION AND FUTURE WORK 5.1 CONCLUSIONS After the process of research, understanding, building , and adjusting the “DESIGN AND IMPLEMENTATION OF AGV COMMODITIES TRANSPORTATION” model of project implementation group, it has operated relatively accurately and it has operated relatively and meet the requirement Specifically, when the camera correctly recognizes the QR code, the system car will start detect lane , almost relatively stable However, there are still some limitations in knowledge and equiqment to be overcome to achieve optimal results The accuracy of the camera when scanning OR codes in lower light and high light intensity is unsatble The system car is not running smoothly if the light not enough 5.2 FUTURE WORK After completing the system and the implementation results in Chapter 4, Project implementation group found the possibility of future development possible, so project implementation group proposed The studied that expand the functions and application of the topic are ass follows: − Adding HMI and the mobile app to convenient for managing purchases and warehouse positions − For a future project and to integrate all processes between production and logistics, an AGV system at unloading finished product at the warehouse should be designed, using AGV Fork lifters In the way, it would be possible a full integration from the beginning of production until the storage at the warehouse − Built-in network module, separate wifi for the automobile, allowing the vehicle to move further − Improve accuracy by Deep Learning 53 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