Smooth tracking controller for AGV through junction using CMU camera

Hội Cơ điện tử Việt Nam Trường Đại học Lạc Hồng (Đơn vị đăng cai tổ chức) Viện Cơ học Tin học ứng dụng, Viện Công nghệ Thông tin, Viện Hàn lâm Khoa học Công nghệ Việt Nam Khu Cơng nghệ cao Thành phố Hồ Chí Minh Chương trình Nghiên cứu Ứng dụng Phát triển Cơng nghệ Cơ khí -Tự động hóa KC-03 Tuyển tập Cơng trình khoa học Hội nghị Cơ điện tử Toàn quốc lần thứ (VCM-2014) Đồng Nai, ngày 21 - 22/11/2014 Nhà xuất Khoa học Tự nhiên Công nghệ Tuyển tập Cơng trình khoa học Hội nghị Cơ điện tử Toàn quốc lần thứ (VCM-2014) ISBN: 978-604-913-306-0 Nhà xuất Khoa học Tự nhiên Công nghệ Địa chỉ: Nhà A16, số 18, đường Hoàng Quốc Việt, Cầu Giấy, Hà Nội Điện thoại:(04) 22149040 Fax: (04)37910147 Email: nxb@vap.ac.vn Dinh Tuyen Nguyen, Van Nho Nguyen, Thanh Vu Tran and Van Vui Nguyen Thiết kế điều khiển nguồn 400 Hz công suất lớn cho máy bay 514 Tăng Quốc Nam and Nguyễn Bá Đại The motion control system of the assistive robot for people with movement disability 521 Le Ngoc Thanh Ha, Thanh Tung Luu, Thien Phuc Tran, Tan Tien Nguyen and Hoang Thai Son Nguyen Study on an Automation Solution for Glue Painting on Shoe Sole 528 Nguyễn Vũ Quỳnh and Trần Hoàng Trung Design and Fabricate the Robot Tennis 536 Pham The Hung Diagnostic of locomotion for off-road mobile robot 541 Nghìn Đặng Văn, Thang Pham, Hà Thái Thị Thu and Dương Nguyễn Minh Giải mã công nghệ thiết kế hệ thống tạo mẫu nhanh lom 549 Nghìn Đặng Văn, Thai Ha, Thang Pham, Dũng Trương Thế and Trung Quang Nhựt Thiết kế, chế tạo khn kênh dẫn nóng cho chi tiết bánh 555 Phạm Bảo Tồn and Nguyễn Ngọc Hải Đánh giá tình trạng khuyết tật cấu trúc dầm phân tích wavelet phổ lượng tín hiệu dao động tự dầm 562 Vũ Hồ Anh and Nghĩa Dương Hoài Control of doubly fed induction generator using internal model control 570 Nghìn Đặng Văn, Thang Pham, Tuấn Huỳnh Việt and Long Gia Giải mã công nghệ thiết kế chế tạo robot vượt địa hình 575 Tuan Trinh Minh and Tien Nguyen Tan Researching and Designing Medical Bed for Obesity Patients 583 Nghìn Đặng Văn, Đại Kiều Nguyễn Phương, Thai Ha and Thức Nguyễn Công Xây dựng thuật toán để xác định phương pháp đánh giá chất lượng thiết bị điện tử y sinh 591 Huu Danh Lam, Tran Duc Hieu Le, Tan Tung Phan, Tan Tien Nguyen and Hoai Quoc Le Smooth Tracking Controller for AGV through Junction using CMU Camera 597 Thanh Hung Tran, Quang Hieu Ngo and Quang Ha Điều khiển vị trí với điều khiển trượt – PID 602 Chanh Nghiem Nguyen, Nhut Thanh Tran and Chi Ngon Nguyen Evaluation of low cost RTK-GPS accuracy for applications in the Mekong Delta 608 Hội nghị Toàn quốc lần thứ Cơ điện tử - VCM-2014 597 Nghiên cứu thiết kế điều khiển bám line cho AGV qua giao lộ Smooth tracking controller for AGV through junction using CMU camera Huu Danh Lam, Tran Duc Hieu Le, Tan Tung Phan and Tan Tien Nguyen Hochiminh City University of Technology, Hochiminh City, Vietnam Hoai Quoc Le Saigon Hi-Tech Park, Vietnam Email : nttien@hcmut.edu.vn Tóm tắt Bài báo đề xuất dạng đường qua giao lộ cho AGV sử dụng CMU camera Sơ đồ tính tốn sai số cho AGV trình bày Mơ hình hóa động học AGV thiết lập, từ xây dựng điều khiển bền vững cho tốn bám đường AGV Kết mơ chứng minh hiệu tính khả thi phương pháp đề nghị Abstract This paper suggests a new path pattern for junction for AGV line tracking using CMU camera The scheme for calculation the tracking error with CMU camera is introduced The system modelling bases on kinematic configuration is given to drive a robust nonlinear controller for AGV line tracking The simulation is done to verify the effectiveness of the proposed method Introduction An automatic guided vehicle (AGV) is a mobile robot that follows markers or wires in the floor, or uses vision, magnets, or lasers for navigation AGVs are most often used in industrial applications to move materials around a manufacturing facility or a warehouse The first AGV was invented by Barrett Electronics in 1953 The AGV can tow objects behind them (or store objects on a bed) in trailers to which they can autonomously attach AGVs are employed in nearly every industry, including, pulp, paper, metals, newspaper, and general manufacturing Transporting materials such as food, linen or medicine in hospitals is also done There are several problems need to concern for design an AGV, such as: navigation, path decision, traffic control, system management, vehicle types, applications, battery management, … There are numbers of research relating to the design, control and implementation of AGV The whole picture of AGV system can be seen in the work of Le Anh Tuan [4] This paper studies on design or robust tracking controller for AGV through junction using CMU camera First, a new path pattern for junction using for AGV line tracking with CMU camera is introduced Then, the scheme for calculation the tracking error with CMU camera is presented The VCM-2014 system modelling bases on kinematic configuration is given to drive a robust nonlinear controller for AGV line tracking The simulation is done to verify the effectiveness of the proposed method Problem Setting 2.1 AVG structure The AGV using in this study is a conventional type of mobile robot platform, which is driven by two driving wheels as shown in the Fig.1 Fig.1 AVG structure using in this paper The tracking point is the center of AGV, it is also the camera position The center of AGV is the middle of two driving wheels Note that, the tracking point and the AGV center is not coincide 2.2 Path pattern The conventional junction path patterns used for AGV can be seen in the Fig.2 For the square-shaped junction, the AGV will stop at the intersection, then rotate in the desired direction That means the AGV speed is not continuous To avoid this problem, the arc-shaped junction is introduced To follow these path patterns, there are numerous of solutions One of the simplest way is using well known CMU camera It provides a vision capabilities to small embedded systems in the form of an intelligent sensor The CMUcam open source programmable embedded color vision sensors are low-cost, low-power sensors for mobile robots It can be used to many different kinds of on-board, real-time vision processing tasks However, for a complex junction such as crossroads (Fig.2, a and b), the application of CMU is difficult To overcome this, this paper proposes a new junctions for using with CMU camera as shown in the Fig.2.c The curve sections is added to provide the ability of smooth tracking for mobile robot when the turn left or right The algorithm for tracking with CMU camera will be stated in the section of this paper DOI: 10.15625/VCM.2014-306 Hội nghị Toàn quốc lần thứ Cơ điện tử - VCM-2014 a Square-shaped junctions b Arc-shaped junctions c Proposed junctions Fig.2 Path patterns using for AGV tracking Controller design 3.1 System modeling To drive the tracking controller for the proposed junction, the system coordinate is introduce as in the following Fig.3 For both directional moving ability, two structures with different position of driving wheels are examined a 𝑑 > b 𝑑 < Fig.3 System coordinate for driving motion of equation with different position of driving wheels The dynamic equation of AGV 𝑥̇ 𝑐𝑜𝑠𝜑 𝑣 � 𝑦̇ � = � 𝑠𝑖𝑛𝜑 0� � � (1) 𝜔 𝜑̇ where 𝑣, 𝜔 are the linear and angular velocities of AGV The dynamic equation of tracking point 𝐶 𝑥̇ 𝐶 = 𝑥̇ − 𝑑𝑠𝑖𝑛𝜑𝜑̇ 𝑦̇ (2) � 𝐶 = 𝑦̇ + 𝑑𝑐𝑜𝑠𝜑𝜑̇ 𝜑̇ 𝐶 = 𝜑̇ where 𝑑 is the distance from center of AGV to the tracking point 𝐶 (also camera position) The dynamic equation of reference point 𝑅 𝑥̇ 𝑅 = 𝑣𝑅 𝑐𝑜𝑠𝜑𝑅 � 𝑦̇ 𝑅 = 𝑣𝑅 𝑠𝑖𝑛𝜑𝑅 (3) 𝜑̇ 𝑅 = 𝜔𝑅 where 𝑣𝑅 is the desired velocity of AGV The controller is designed for the tracking point 𝐶 to track the target point 𝑅 in the reference path with the desired velocity 𝑣𝑅 To this, let’s define the tracking error as the following 𝑒1 𝑐𝑜𝑠𝜑 𝑠𝑖𝑛𝜑 𝑥𝑅 − 𝑥𝐶 (4) �𝑒2 � = �−𝑠𝑖𝑛𝜑 𝑐𝑜𝑠𝜑 0� � 𝑦𝑅 − 𝑦𝐶 � 𝑒3 0 𝜑𝑅 − 𝜑𝐶 VCM-2014 598 After some calculations, the error dynamics can be derived as follows 𝑣𝑅 𝑐𝑜𝑠𝑒3 𝑒̇1 −1 𝑒2 𝑣 �𝑒̇2 � = � 𝑣𝑅 𝑠𝑖𝑛𝑒3 � + � −𝑑 − 𝑒1 � � � (5) 𝜔 𝜔𝑅 𝑒̇3 −1 In the case the AGV moves to the reverse direction, the equation is still available with replace 𝑑 by −𝑑, that means 𝑑 is positive or negative depending on the moving direction of AGV 3.2 Controller Design Theorem: The system (5) is stabilized by the following tracking controller 𝑣 = 𝑣𝑅 𝑐𝑜𝑠𝑒3 + 𝑘1 𝑒1 � (6) 𝜔 = 𝑘2 𝑣𝑅 𝑒2 + 𝜔𝑅 + 𝑘3 𝑠𝑖𝑛𝑒3 Proof Choose the Lyapunov’s function 1 − 𝑐𝑜𝑠𝑒3 𝑉 = 𝑒12 + 𝑒22 + ≥0 𝑘2 where 𝑘1 , 𝑘2 , 𝑘3 are positive values Its derivative yields 𝑉̇ = 𝑒1 (𝑣𝑅 𝑐𝑜𝑠𝑒3 − 𝑣) 𝑠𝑖𝑛𝑒3 + (𝑘2 𝑣𝑅 𝑒2 + 𝜔𝑅 − 𝜔) 𝑘2 The controller (6) leads to achieve the negative of 𝑉̇ That means the system (5) is stable with the tracking controller (6) in the sense of Lyapunov’s stability, and all tracking errors 𝑒1 , 𝑒2, 𝑒3 will be converged to zero as 𝑡 → ∞ In the tracking controller (6), when starting with 𝑣0 ≈ 𝑣𝑅 , the error 𝑒1 can be set to be zero (or small enough to be ignored) resulting on the measuring errors 𝑒2 , 𝑒3 as shown in the next section Measure tracking error with CMU camera In this section, together with the proposed path patterns, the CMU camera is used for measuring the tracking errors 𝑒2 , 𝑒3 Fig.4 Errors measuring scheme form CMU camera frame The CMU camera sensor outputs are the path captured frame and the center of captured path, from which we can calculate (𝑥1 , 𝑦1 ), (𝑥2 , 𝑦2 ) and (𝑥3 , 𝑦3 ) Then the errors can derived as follows 𝑒 = 𝑘(160 − 𝑥3 ) (7) � 𝑒3 ≈ 𝑘(𝑥2 − 𝑥1 − 𝑏/𝑘)/200 where 𝑘 is the conversion factor between the real length and camera pixel Hội nghị Toàn quốc lần thứ Cơ điện tử - VCM-2014 599 In case of multi-path (at the proposed crossroads), the signal will be shifted with the designed color Because each line has the same width of 𝑏, the measured errors can be modified as follows 𝑒 = 𝑘(160 − 𝑥3 ) ∓ 𝑏 (8) � 𝑒3 ≈ 𝑘(𝑥2 − 𝑥1 − 𝑏/𝑘)/200 Simulation Results and Discussion The proposed method is verified by the mean of simulation The AGV will be controlled using the controller (6) with the tracking error calculated from (8) for both tracking line as shown in the Fig.6 b Path following of AGV a The proposed tracking line b Normal tracking line Fig.6 Two cases of tracking line for simulation study The parameters of AGV using in the simulation are given in the Table.1 Table The parameters using for simulation study Name Value Unit Width of AGV 350 𝑚𝑚 Length of AGV 230 𝑚𝑚 Wheel diameter 70 𝑚𝑚 Wheel distance 220 𝑚𝑚 Width of the tracking line, 𝑏 𝑚𝑚 Curve radius of the tracking line 412 𝑚𝑚 0.82 AGV velocity, 𝑣𝑟 𝑚/𝑠 Distance from tracking point to 130 𝑚𝑚 AVG center, 𝑑 c Wheels velocity as input AGV Fig.7 Simulation results for proposed tracking method The simulation results are shown in the Fig.7 for the proposed tracking method and Fig.8 for conventional tracking a Tracking error 𝑒𝑖 a Tracking error 𝑒𝑖 b Path following of AGV VCM-2014 Hội nghị Toàn quốc lần thứ Cơ điện tử - VCM-2014 c Wheels velocity as input AGV Fig.7 Simulation results for normal tracking From the results as shown in the Fig.6.a and Fig 7.a, the tracking errors 𝑒𝑖 are almost the same for both case of tracking lines, except at the shifting tracking point between straight and curve line (near 1𝑠 and 1.8𝑠) At this point, the control inputs (driving motor speed) was required higher for keeping AGV to follow the reference line as shown in the Fig.6.b and Fig.7.b In both cases, the AGV can track the reference line robustly as shown in the Fig.6.c and Fig.7.c Conclusion This paper presents the studies on design or robust tracking controller for AGV through junction using CMU camera This is a part of the Restaurant Service Robot Project, which is studying at HiTech Mechatronics Lab at Hochiminh City University of Technology A new path pattern for junction using for AGV line tracking with CMU camera is introduced The scheme for calculation the tracking error with CMU camera is presented The system modelling bases on kinematic configuration is given to drive a robust nonlinear controller for AGV line tracking The simulation results prove that the proposed method can be used for control the AGV through complex junction with CMU camera The experiment is studying and we hope it will be further proof for the proposed method Tài liệu tham khảo [1] Wu Xing et al., Intersection Recognition and Guide-path Selection for a Vision-based AGV in a Bidirectional Flow Network, Int’l Journal of Advanced Robotic Systems, DOI: 10.5772/58218, pp 1-17, 2014 [2] M Sharma, Control Classification of Automated Guided Vehicle Systems, Int’l Journal of Engineering and Advanced Technology (IJEAT), Vol.2, Issue.1, pp.2249–8958, 2012 [3] P.T Doan, et al., Path Tracking Control of Automated Guided Vehicle Using Camera Sensor, Proc of The 2011 Int’l Symposium on Automotive and Convergence Engineering, pp 89-94, Vietnam, January 19-21, 2011 [4] T.L Anh et al., A Review of Design and Control of Automated Guided Vehicle Systems European Journal of Operational Research, Vol 171, Issue 1, pp.1-23, 2006 VCM-2014 600 [5] T.T Nguyen et al., Tracking Control of a Spot Bead Welding Mobile Robot Using Camera Sensor, Proc of The 2003 International Symposium on Advanced Engineering (ISAE’03), Pusan, Korea, pp 408-414, November 2003 [6] T.L Chung et al., A Chattering-Free Sliding Mode Control of Two-Wheeled Welding Mobile Robot for Tracking Smooth Curved Welding Path, Proc of The Int’l Symposium on Mechatronics’03 (ISM’03), Hochiminh City, Vietnam, pp 1-8, September 2003 [7] T.L Chung et al., Backstepping-Based Nonlinear Controller of a Two-Wheeled Mobile Robot Tracking Smooth Curved using USB Camera, Proc of The Int’l Symposium on Mechatronics’03 (ISM’03), Hochiminh City, Vietnam, pp 39-45, September 2003 [8] T.H Bui et al., Nonlinear Adaptive Control for Tracking Trajectory of a Two-Wheeled Welding Mobile Robot, Proc of The Int’l Symposium on Mechatronics’03 (ISM’03), Hochiminh City, Vietnam, pp 120-125, September 2003 [9] T.L Chung et al., Control of Two-Wheeled Mobile Robot Tracking Complicated Curvature Wall, Proc of the Korean Society for Power System Engineering 2002 Spring Annual Meeting (KSPSE’2002), Cheju, Korea, pp 196-202, May 10-11, 2002 Lam Huu Danh was born in Viet Nam on October 30, 1979 He received the B.S degrees from Faculty of Mechanical Engineering, Ho Chi Minh City University of Technology (HCMUT), Viet Nam in 2001 He received the M.S degrees from Faculty of Information, Media and Electrical Engineering, Cologne University of Applied Sciences, Germany on October, 2008 He works at Saigon Port, Ho Chi Minh City, Viet Nam His research Interests are Automation and Optimization method including industrial applications Tran Duc Hieu Le was born in Viet Nam on May 25th, 1986 She is M.S student at the Department of Mechatronics at HCMUT Her interests is mobile robot control and application Tan Tung Phan was born in Viet nam on May 3th, 1959 He received the B.S and M.S degrees from the Faculty of Mechanical Engineering, HCMUT, Vietnam in 1982 and 1995 He received Ph.D degree from Dept of Mechanical Engineering, Pukyong Nat’l Hội nghị Toàn quốc lần thứ Cơ điện tử - VCM-2014 University, Pusan, Korea in February, 2005 He is a senior lecturer of the Faculty of Mechanical Engineering, HCMUT His fields of interest are Robot Control and Welding Automation Process Control Tan Tien Nguyen received the B.S degree in Mechanical Engineering from HCMUT, Vietnam, in 1990 and the M.S degree and Ph.D degree in Mechanical Eng., Pukyong Nat’l University, Pusan, Korea, in August, 1998, and August, 2001, respectively Now he is an Ass Professor at the Faculty of Mechanical Engineering, HCMUT His interests are robust control theory and industry automation control VCM-2014 601 ... camera First, a new path pattern for junction using for AGV line tracking with CMU camera is introduced Then, the scheme for calculation the tracking error with CMU camera is presented The VCM-2014... Square-shaped junctions b Arc-shaped junctions c Proposed junctions Fig.2 Path patterns using for AGV tracking Controller design 3.1 System modeling To drive the tracking controller for the proposed junction, ... of Technology A new path pattern for junction using for AGV line tracking with CMU camera is introduced The scheme for calculation the tracking error with CMU camera is presented The system modelling