MINISTRY OF EDUCATION AND TRAINING HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION GRADUATION PROJECT MAJOR AUTOMATION AND CONTROL ENGEERING TECHNOLOGY AUTONOMOUS NAVIGATING QUADCOPTER FOR PACKAGE DELIVERY APPLICATION LECTURER: LÊ MỸ HÀ , Ph. STUDENT: LÊ HUY PHƯƠNG SKL 0 0 9 7 5 4 Ho Chi Minh City - January 2023 HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION FACULTY FOR HIGH QUALITY TRAINING GRADUATION PROJECT AUTONOMOUS NAVIGATING QUADCOPTER FOR PACKAGE DELIVERY APPLICATION LÊ HUY PHƯƠNG - 18151030 Major: AUTOMATION AND CONTROL ENGEERING TECHNOLOGY Advisor: LÊ MỸ HÀ, Assoc. Phd Ho Chi Minh City, January 2023 THE SOCIALIST REPUBLIC OF VIETNAM Independence – Freedom– Happiness -------- Ho Chi Minh City, January 6th, 2023 GRADUATION PROJECT ASSIGNMENT Student name: Lê Huy Phương Student ID: 18151030 Major: Automation and Control Class: 18151CLA1 Engineering Technology Advisor: Assoc. Lê Mỹ Hà Phone number: 0938811201 Date of assignment: Date of submission: 1.
Project title: Autonomous navigating quadcopter for package delivery application 2. Initial materials provided by the advisor: - Documents and articles related to system control and image processing - The related thesis of previous students. - The hardware specifications and its review. Content of the project: - Read, perform surveys, summarize to determine the scope of the project.
- Research the theoretical array math related to trajectory tracking for quadcopter to give directions and solutions during design - Read and process sensors signal. - Write program to control microcontroller. - Research tracking controller algorithm for quadcopter. - Write project report.
- Prepare slide for presenting. Final product: The quadcopter can operate inside HCMUTE school campus based on a combination of camera, GPS, IMU and LIDAR 1D in Auto mode under not too complex conditions. 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, January 30th, 2022 ADVISOR’S EVALUATION SHEET Student name: Lê Huy Phuong Student ID: 18151030 Major: Automation and Control Engineering Technology Project title: Autonomous navigating quadcopter for package delivery application Advisor: Assoc. Lê Mỹ Hà EVALUATION 1.
Content of the project: - The content of this report is 72 pages. - The design and construction of quadcopter can perform trajectory tracking and self-localizing inside HCMUTE campus. - The system runs based on a series of different sensors and algorithms. - The final product meets the requirements in the proposal.
Strengths: - The author proposed a method for researching, constructing and navigating Quadcopter. - The final product meets the requirements and success to follow several desired trajectories. Weaknesses: - The author should present more detailed information about the accuracy of the proposed method in experiments 4. Approval for oral defense? (Approved or denied) .) Ho Chi Minh City, December 30th, 2022 ADVISOR (Sign with full name) ii THE SOCIALIST REPUBLIC OF VIETNAM Independence – Freedom– Happiness -------- EVALUATION SHEET OF DEFENSE COMMITTEE MEMBER Student name:.
Name of Defense Committee Member:. Content and workload of the project .) Ho Chi Minh City, January 6th, 2023 COMMITTEE MEMBER (Sign with full name) iii ACKNOWLEDGEMENTS The author specially would like to express gratefulness to Professor Lê Mỹ Hà for his thoughtful instructions which provide enough information to make the right decisions in this thesis. Furthermore, the author sincerely thanks all members of IS lab for valuable knowledge and experience they shared in order to gain the full perspective of this project. The author would also like to extend gratitude for Faculty of High Quality Training and Faculty of Electrical and Electronics Engineering where basic knowledge and experience is obtained carefully.
The author would like to thank to family for their support of the team throughout the working of this thesis. Sincere thanks for everything! iv ABSTRACT This thesis proposes a self-navigating algorithm for autonomous quadcopter to perform the act of path-following as an example of one action of shipping and transportation. The project will focus on proposing method related to trajectory tracking guidance that controls the yaw positions of the quadcopter by forcing the direction of velocity converge to a reference line pointing to the trajectories. To navigate the vehicle using GPS signals, waypoint analyzing is designed to steer the vehicle using GPS with respect to a designated GPS track.
Before that, mathematical model of the quadcopter is presented as a facility to design Proportion Integrate Derivative control lately. Also, an algorithm for increasing accuracy quadcopter position is introduced based on the use of computer vision. The assessments will cover two sections: simulation parts are carried out and show the good performance of trajectory tracking abilities; practical experiments are carried out and show the behavior of quadcopter when the system received external factors in outdoors. v TABLE OF CONTENT ACKNOWLEDGEMENTS.
v TABLE OF CONTENT. vi LIST OF FIGURES. x LIST OF TABLES. xv CHAPTER 1: INTRODUCTION.
3 CHAPTER 2: FUNDERAMENTAL THEORY. Force and movement. Localization control system on 3D environment method. Altitude stabilization method.
Positioning stabilization method. Mathematical approach of locking quadcopter’s position at a fixed point. Keypoint tracking algorithm to improve performance using Optical Flow. Keypoint detection algorithm.
Optical flow algorithm. Trajectory tracking algorithm. Trajectory tracking guidance. Waypoints allowance’s zone.
Preprocessing of raw signal data. Overview of Kalman filter algorithm. One-dimensional Kalman-filter. Technologies used in autonomous navigating quadcopter.
Introduction to LIDAR technology. Working principle of LIDAR 1D .1 Overview of image processing. Types of Image Processing. Fundamental Image Processing Steps.
Image processing applications. Advantages of image processing. The use of image processing related to topic. Global Positioning System.
Inertial Measurement Unit. 27 CHAPTER 3: SYSTEM CONSTRUCTION. Structure of quadcopter. 250 Quadcopter Frame ZMR Carbon.
Brushless motors MT2204. Working and control principle. Motor brushless MT2204- 2300kv. GPS module Beitian BN-880.
Matek PDB plus XT60 connector. DC-DC converter output 5V 3A USB type A. Power supply pin LiPo .2 Understanding LiPo specifications .3 Hardware sketch’s assembly. Hardware pins configurations.
Hardware overall combination. 49 CHAPTER 4: DESIGN AND CALCULATION. PD algorithm implementation. Robot Operating System.
Building ROS for quadcopter. Flowchart of attitude stabilization algorithm. Flow chart of self-localizing 2D quadcopter using PID algorithm.3 Flowchart of trajectory tracking algorithm. 59 CHAPTER 5: RESULTS AND ASSESSMENTS.
Raw signal data preprocessing. Self-localizing on 3D environment under the impact of wind intensity. Trajectory tracking pattern. Performance results in simulations.
Performance results in practical experiment. 66 CHAPTER 6: CONCLUSION AND DISCUSSION. 73 ix LIST OF FIGURES FIGURE 1 RESEARCH ON EVOLVING OF UAV. 1 FIGURE 2 PROJECTED WORLDWIDE MARKET GROWTH FOR COMMERCIAL DRONES.
2 FIGURE 3 INCREASING OR DECREASING THE SPEEDS OF ALL FOUR ROTORS SIMULTANEOUSLY CONTROLS THE COLLECTIVE THRUST. 4 FIGURE 4 CHANGE RELATIVE SPEED OF THE RIGHT AND LEFT ROTORS. 5 FIGURE 5 CHANGE RELATIVE SPEED OF THE FRONT AND BACK ROTORS. 5 FIGURE 6 SPEED OF CLOCKWISE ROTATING PAIR AND COUNTER-CLOCKWISE ROTATING PAIR.
5 FIGURE 7 EULER ANGLES. 6 FIGURE 8 PID CONTROL. 9 FIGURE 9 ALTITUDE STABILIZATION. 9 FIGURE 10 KEYPOINT DETECTION ALGORITHM ASSESSMENT.
THE GREEN AREA IN THE MAP DENOTES THE POTENTIAL CORNER. 13 FIGURE 12 GEOMETRY STRATEGY OF TRAJECTORY TRACKING ALGORITHM. 14 FIGURE 13 BLOCK DIAGRAM FOR ONE-DIMENSION KALMAN FILTER. 18 FIGURE 14 LIDAR TECHNOLOGY.
20 FIGURE 15 WORKING PRINCIPLE OF LIDAR 1D SKETCH. 21 FIGURE 16 MEDICAL IMAGE RETRIEVAL. 23 FIGURE 17 THE USE OF TRAFFIC SENSING TECHNOLOGIES. 24 FIGURE 18 THE USE OF IMAGE RECONSTRUCTION.
24 FIGURE 19 FACE DETECTION ALGORITHM. 25 FIGURE 20 THE USE OF VISION SENSOR OF QUADCOPTER IN ARCHITECTURE. 26 FIGURE 21 PROCESSING OF INCREASING IMAGE’S INTENSITY. 26 FIGURE 22 WORKING PRINCIPLE OF GPS SKETCH.
27 FIGURE 23 IMU COMPONENTS. 27 FIGURE 24 FLIGHT COMPUTER AND FLIGHT CONTROLLER CONNECTION STRUCTURE. 29 FIGURE 25 BLOCK DIAGRAM OF FLIGHT COMPUTER AND FLIGHT CONTROLLER. 29 FIGURE 26 250 QUADCOPTER FRAME.
30 FIGURE 27 FRAME ASSEMBLY INSTRUCTIONS. (A) GENERAL VIEW OF FLIGHT CONTROLLER. 33 FIGURE 30 PINS IN SCHEME. 33 FIGURE 31 BAROMETER BMP280.
34 FIGURE 32 STM32F05 ON TWO VIEWS. (A) SHOWS THE CHIP ON THE VIEW OF PRODUCT. (B) SHOW PINOUT DIAGRAM. 35 FIGURE 33 RASPBERRY PI.
36 x FIGURE 34 BLDC MOTOR THREE-PHASE STRUCTURE. 37 FIGURE 35 HALL SENSOR POSITION IN BLDC MOTOR. 38 FIGURE 36 MOTOR BRUSHLESS MT2204- 2300KV. 38 FIGURE 37 SOME OF ESC IN MARKETS.
39 FIGURE 38 ESC WORKING PRINCIPLE. 40 FIGURE 39 HALL-EFFECT SENSORS OUTPUT. 40 FIGURE 40 BACK EMF. 41 FIGURE 41 ESC ONEMODEL 2S-5S 35A DSHOT600 BLHELI-S.
41 FIGURE 42 ESC PROTOCOL SPEED COMPARISON. 42 FIGURE 43 CAMERA LOGITECH C270. 43 FIGURE 44 TF LUNAR SENSOR. 43 FIGURE 45 BEITIAN BN-880.
44 FIGURE 46 MATEK PDB PLUS XT60 CONNECTOR PINOUT DIAGRAMS. 45 FIGURE 47 DC-DC CONVERTER OUTPUT 5V 3A USB TYPE A. 45 FIGURE 48 SOME OF LIPO BATTERY FOUND IN MARKETS. 46 FIGURE 49 TATTU 2300MAH 3S 45C 11.
47 FIGURE 50 QUADCOPTER’S FANS. 47 FIGURE 51 PINS I/O CONFIGURATIONS. 49 FIGURE 52 COMPONENTS’ POSITION ON THE HARDWARE. 49 FIGURE 53 PROGRAMING FOR PD.
50 FIGURE 54 ROS IS UTILIZED AS VIRTUAL ALGORITHM APPLICATION FOR AUTONOMOUS VEHICLE. 51 FIGURE 55 ROS COMMUNICATION BETWEEN SUBSCRIBER AND PUBLISHER. 52 FIGURE 56 ROS FOR QUADCOPTER. 53 FIGURE 57 ONE SERIAL OF DATA STRUCTURE OF MAVLINK.
53 FIGURE 58 FLOWCHART OF ENTIRE SYSTEM PROCESS. 54 FIGURE 59 ATTITUDE STABILIZATION ALGORITHM. 56 FIGURE 60 FLOW CHART OF SELF-LOCALIZING ALGORITHM USING PD CONTROLLER WITH TWO TYPE INPUTS. 57 FIGURE 61 FLOWCHART OF FINDING TRANSLATION VECTORS ALGORITHM.
58 FIGURE 62 DETERMINING TRANSLATION VECTOR PROCESS. 58 FIGURE 63 FLOW CHART OF TRAJECTORY TRACKING ALGORITHM, COMBINING SELF- LOCALIZING ALGORITHM. 59 FIGURE 64 RESULTS OF KALMAN FILTER ALGORITHM PERFORMANCE. 61 FIGURE 65 RESULTS OF SELF-LOCALIZING IN PRACTICAL CONDITION UNDER SMALL WIND INTENSITY IN PRACTICAL EXAM.
(A) SHOWS THE TESTING IN OUTDOORS. (B) SHOWS POSITIONING FROM TOP OF VIEW. 61 FIGURE 66 RESULTS OF OPTICAL FLOW ALGORITHM. (A) IS AN ORIGINAL FRAME, (B) IS THE GRAY IMAGE, (C) IS ORIGINAL FRAME CONTAINING KEYPOINTS.
(D) IS xi ORIGINAL FRAME CONTAINING TRANSLATION VECTORS FROM THOSE KEYPOINTS. 62 FIGURE 67 RESULTS OF OPTICAL FLOW ALGORITHM. (A) IS AN ORIGINAL FRAME, (B) IS THE GRAY IMAGE, (C) IS ORIGINAL FRAME CONTAINING KEYPOINTS. (D) IS ORIGINAL FRAME CONTAINING TRANSLATION VECTORS FROM THOSE KEYPOINTS.
62 FIGURE 68 VIEW ON GOOGLE MAP. 63 FIGURE 69 SIMULATION RESULTS OF LADDER LINE. (A) ILLUSTRATES THE PERFORMANCE IN 3D SPACE. (B) IS SIMULATION RESULT OF PITCH ANGLE.
(C) IS SIMULATION RESULT OF THE ROLL ANGLE. (D) IS SIMULATION RESULT OF THE YAW ANGLE. 64 FIGURE 70 SIMULATION RESULTS OF PERPENDICULAR LINE. (A) ILLUSTRATES THE PERFORMANCE IN 3D SPACE.
(B) IS SIMULATION RESULT OF PITCH ANGLE. (C) IS SIMULATION RESULT OF THE ROLL ANGLE. (D) IS SIMULATION RESULT OF THE YAW ANGLE. 64 FIGURE 71 SIMULATION RESULTS OF RANDOM LINE.
(A) ILLUSTRATES THE PERFORMANCE IN 3D SPACE. (B) IS SIMULATION RESULT OF PITCH ANGLE. (C) IS SIMULATION RESULT OF THE ROLL ANGLE. (D) IS SIMULATION RESULT OF THE YAW ANGLE.
65 FIGURE 72 SIMULATION RESULTS OF HOURGLASS LINE. (A) ILLUSTRATES THE PERFORMANCE IN 3D SPACE. (B) IS SIMULATION RESULT OF PITCH ANGLE. (C) IS SIMULATION RESULT OF THE ROLL ANGLE.
(D) IS SIMULATION RESULT OF THE YAW ANGLE. 65 FIGURE 73 SIMULATION RESULTS OF ZIGZAG PATTERN TYPE 2. (A) ILLUSTRATES THE PERFORMANCE IN 3D SPACE. (B) IS SIMULATION RESULT OF PITCH ANGLE.
(C) IS SIMULATION RESULT OF THE ROLL ANGLE. (D) IS SIMULATION RESULT OF THE YAW ANGLE. 66 FIGURE 74 RESULT OF MOVING LADDER TRAJECTORY PATTERN. 66 FIGURE 75 LADDER TRAJECTORY IN PRACTICAL CONDITION AND SIMULATION RESULT COMPARISON.
67 FIGURE 76 RESULT OF MOVING PERPENDICULAR TRAJECTORY PATTERN.