A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype

Juan C. Tejada; Alejandro Toro-Ossaba; Santiago Muñoz Montoya; Santiago Rúa

doi:10.1155/2022/7712312

A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype

Tejada, Juan C.;Toro-Ossaba, Alejandro;Muñoz Montoya, Santiago;Rúa, Santiago 2022-03-21 00:00:00 Hindawi Journal of Robotics Volume 2022, Article ID 7712312, 13 pages https://doi.org/10.1155/2022/7712312 Research Article A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype 1 1 1 Juan C. Tejada , Alejandro Toro-Ossaba , Santiago Muñoz Montoya , and Santiago Ru ´ a Faculty of Engineering Department of Mechatronics, Universidad EIA Envigado, Medell´ın, Colombia Electronics and Telecommunications Engineering Department, Universidad de Medell´ın, Medell´ın, Colombia Correspondence should be addressed to Juan C. Tejada; juan.tejada@eia.edu.co Received 5 January 2022; Accepted 25 February 2022; Published 20 March 2022 Academic Editor: L. Fortuna Copyright © 2022 Juan C. Tejada et al. %is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. %is paper addresses the mechanical and electrical design of an autonomous guided vehicle (AGV) test prototype based on a systems engineering approach. First, the diﬀerent phases of the systems engineering approach are described. %e conceptual design begins with the house of quality, which weighs the relevance of each user requirement and ends with a functional representation of the vehicle. %en, the mechanical and electrical design are presented considering diﬀerent subsystems such as the chassis, cargo platform, suspension system, power, and control components. Finally, diﬀerent tests were carried out on the prototype, validating its movement and load capacities. %e systems engineering approach as a methodology for the construction of complex systems has proven to be an excellent tool for the development of autonomous guided vehicles. technologies such as mobile robots [9]. %ese robots can 1. Introduction perform diﬀerent movements and tasks within industrial Nowadays, smart manufacturing is the evolution from environments, allowing greater ﬂexibility and scalability in traditional factories to fully connected, ﬂexible, and diﬀerent processes [10, 11]. reconﬁgurable systems that can easily adapt to frequently Mobile robots can be divided into three categories [12] changing product and production requirements [1]. %is according to their moving mechanism: wheeled [13–15], ﬂexible manufacturing oﬀers greater capacity to produce legged [16–18], or hybrid [19, 20]. Wheeled robots, and in goods on a modular system, rather than the traditional linear particular autonomous guided vehicles (AGVs), are widely one [2], allowing to select which processes or tasks are used in industrial environments due to their simplicity and performed without the need of reconﬁguring the whole few actuators, making them a very important component of smart factories and smart logistics [21]. process [3]. Over the past decades, ﬂexibility has become one of the Regarding the development and manufacturing of AGVs determinant factors in logistics and production system in the last ten years, Peng and others [22] designed a material design, particularly Industry 4.0 as been identiﬁed has a conveying mobile robots with a four-wheel driven chassis determinant factor in the evolution of ﬂexible and omnidirectional mobility. Li and others [23] proposed manufacturing, bringing emerging technologies that allow diﬀerent mecanum wheel conﬁgurations for omnidirec- the decentralization and ﬂexibility needed to transform the tional mobile robots based on topological design methods. traditional production environment [4–8]. %is emergence Tamara and others [24] proposed a new low-cost electronic of Industry 4.0, smart manufacturing, ﬂexible systems, and system for an AGV type forklift. Zhang and Henke [25] built logistics has also motivated the development of new a new AGV based on a mechatronic development cycle 2 Journal of Robotics accounting for user requirements, modeling, synthesis, allows to map the user’s needs into a ﬁnal product [36]. among other phases. Aloui and others [26] developed a Figure 1 presents the steps of such methodology. design methodology for AGVs with two phases: a top-down %is research was only developed until the initial stages phase containing user requirements, functional description, of the testing and reﬁnement phase; this is because the aim and structural modeling; and a bottom-up phase for the was to develop a working prototype. Future work will focus integration and implementation of the models. on the reﬁnement stage. Nowadays, many of the technologies start with the idea of building a complex system or having the ﬁnal solution 2.1. Phase 0: Planning. %e planning phase is an essential rather than having a clear problem deﬁned [27]. It is im- part of the product design life cycle. In this stage, an in- portant to have a methodology that allows mapping the vestigation and scoping of the product is carried out; this needs of interested parties in functional requirements, which investigation normally includes searching for the state of the serves as the basis for the construction of a viable techno- art related to the topic, the potential market for the product, logical solution [28]. To use a clear methodology for complex a ﬁnancial analysis for the next phases, and the product systems allows you to have a track record of the decisions, beneﬁts and possible issues. %e idea of this vehicle arises even when the result of the system is not as expected or has from the need to generate appropriation of knowledge in the imperfections [29]. Systems engineering is a multidisci- construction of autonomous vehicles to impact the plinary approach to the design, manufacture, operation, and Colombian robotic industry with the development and retirement of a complex system such as an autonomous commercialization of new kinds of AGV robotic systems for vehicle [30], aircrafts [31], manufacturing automation [32], industrial environments. and other kinds of machines [33]. For instance, Aristizabal and others [34] presented a modular hardware architecture for an ROV based on systems engineering. Sadraey [31] 2.2. Phase 1 and Phase 2: Concept Development and System- provides a guide for aircraft design based on an engineering Level Design. Phase 1 and phase 2 are generally addressed system considering diﬀerent systems such as wing, tail, and together and correspond to the conceptual design stage. propulsion. Tagliaferri and others [35] proposed an evalu- Phase 1, known as concept development, considers the ation of the life cycle of electric and hybrid vehicles based on diﬀerent ways the product and each subsystem can be a systems engineering approach. designed [36]; this phase generally takes what was learned %is research presents the mechanical, electrical, and during the planning phase and also new data acquired from software development of an omnidirectional autonomous surveys, focus groups, benchmarking, and the quality guided vehicle (AGV) testing prototype, which will be used function deployment (QFD); a common tool used in this in future work for the implementation and testing of au- phase is the house of quality (HoQ), which allows to deﬁne tonomous navigation algorithms using robot operating the priority of the user requirements and engineering system (ROS) to validate its scalability in an industrial characteristics of the product. Section 3.1 presents the QFD environment. %e main contribution of this research is the and an overview of the concept development. use of systems engineering as a methodology or tool in the Phase 2, known as the system-level design, is where the development of an autonomous guided vehicle for the in- functions of the product are examined, leading to the di- dustry. %is AGV was developed to reduce the develop- vision of the product into various subsystems [36]. In this mental gap of mobile robots applied to the industry in phase, all the subsystems are deﬁned and arranged into a Colombia. %e organization of the paper is as follows: product architecture, and also the interfaces between sub- Section 2 presents the methodology used in the mechanical, systems are deﬁned. %is is the phase where the product or electrical, and software development of the vehicle; Section 3 prototype begins to take shape. %is phase is addressed in describes the conceptual design of the vehicle taking into Section 3.2. account stakeholder requirements; Section 4 presents the mechanical, electrical, and software design of the vehicle; 2.3. Phase 3: Detail Design. Phase 3, known as detail design, Section 5 contains some tests and results carried out in the is where the design is brought to the state of a complete AGV; and Section 6 presents some conclusions and future engineering description of a tested and producible product directions for the AGV. [36]. In this stage, all the subsystems proposed in phase 2 are designed in detail in order to meet the user requirements 2. Systems Engineering Methodology deﬁned in phase 1. In the case of this research, this phase includes the detail mechanical design of the AGV prototype An autonomous guided vehicle (AGV) is a complex system; in Section 4.1; the vehicle kinematics and position estimation therefore, every part of its design must be planned in detail. algorithm in Sections 4.2 and 4.3, respectively; the detailed A roadmap allows for a clear understanding of the system electrical design in Section 4.4; and the control system life cycle and a ﬁnal product that meets deﬁned user re- implemented in the vehicle in Section 4.5. quirements. To do this, a series of design stages must be performed, beginning with general planning, followed by concept development, system-level and detail design, test- 2.4. Phase 4: Testing and Reﬁnement. %e last phase addressed in this research is phase 4, known as testing and ing, reﬁnement, and the production ramp-up. %e systems engineering approach to the design of complex systems reﬁnement; this phase consists in testing the developed Journal of Robotics 3 Phase 1 Phase 2 Phase 4 Phase 5 Phase 0 Phase 3 Concept System-level Testing and Production Planning Detail Design Development Design Refinement Ramp-up Figure 1: Product development process [36]. prototype in order to verify that it fulﬁlls the user re- (3) Rigidity of suspension springs quirements deﬁned in phase 1. Once the prototype is tested, (4) Motor torque the results are reviewed to determine if the prototype is ready (5) Vehicle speed for production or whether it is necessary to perform further (6) Assembly and disassembly time reﬁnement prior to production. As mentioned earlier that the scope of this research ended in the testing phase of the (7) Degrees of freedom prototype, future work will address the reﬁnement stage on (8) Adhesion of the payload contact area phase 4 and will increase the scalability of the vehicle, closing (9) Wear resistance the gap between a testing prototype and an industrial (10) Vehicle size product. %e testing performed on the AGV prototype along with the results of those tests can be found in Section 5. (11) Probability of blocking (12) Braking time when detecting an obstacle 3. Conceptual Design (13) Vehicle acceleration (14) Payload contact area %is section presents both the concept development and the system-level design of the AGV prototype. It covers the (15) Accuracy in estimating position within the facilities analysis of the user requirements and engineering charac- With the requirements and the characteristics identiﬁed, teristics using the house of quality (HoQ) tool and the it is now possible to implement the house of quality (HoQ) system-level design in which all the AGV subsystems are presented in Figure 2. depicted in a functional representation. 3.2. System-Level Design. After having the appropriate en- 3.1. Quality Function Deployment (QFD). %e QFD is a tool gineering characteristics in mind, the next step is to make a used by a wide variety of companies to design a product functional representation of the vehicle that is going to be based on the requirements of its users; this tool generates an made. Systematic design is a method that provides a way to understanding of the problem and common terms for the describe a system or product in a general form based on its entire work team, helping in the generation of concepts and main functions, in which each subsystem is taken as a box the selection of the engineering characteristics that best meet that transforms energy, material, and signals to obtain the the needs of customers and stakeholders. %e QFD consists desired output [36]. Figure 3 presents the functional rep- of several phases throughout the development of the resentation of the AGV prototype that describes the main product; this investigation only carried out initial one, which functions of the system. corresponds to the HoQ following the methodology used by With the functional representation, several concepts U.S. companies [36]. were presented and discussed to address each one of the functions required for the system. %e concept selection was 3.1.1. House of Quality (HoQ). %ere are many ways to made using a selection matrix following Dieter’s method- design an HoQ as it has diﬀerent rooms, each with a par- ology [36]. An evaluation of how much the proposed ticular function. %e principal rooms for this research were concepts fulﬁlled the engineering characteristics and user those corresponding to user requirements and engineering requirements was realized, and the selected concept was the characteristics, which were analyzed through the relation- one with greater score among those proposed. ship matrix, resulting in the importance ranking to consider in the design phase. Table 1 speciﬁes each of the customer 4. Detail Design requirements and its description. %ese requirements are based upon past experiences of %is section presents the detail design of the subsystems the previous products and the stakeholders’ needs for future proposed in the conceptual design. First, the mechanical developments. For the next step, it is important to translate design is presented along with the kinematic model of the these needs into measurable values, and this was accom- vehicle and the proposed position estimation algorithm. plished by reviewing the competitor’s characteristics and Finally, the electrical design is presented along with the analyzing other factors that could intervene in the devel- proposed control system. opment process; the following list enumerates the ones chosen: 4.1. Mechanical Design. %e AGV was conceived as a testing (1) Rigidity of the shell material prototype with the purpose of validating its capabilities as an (2) Number of tools required for maintenance industrial platform. %e system includes in its design 4 Journal of Robotics Table 1: Customer requirements. Requirement Description Shock and scratch %e system is resistant to shocks and scratches that can be caused in normal factory operation. resistant %e system can be moved anywhere in the facility without the need for modiﬁcations or installation of auxiliary Autonomy systems. Payload displacement %e system can move a payload of up to 150 kg. Reliability %e system can recover automatically after detecting an obstacle. Safety %e system is safe to work together with the operators. Easy maintenance %e system can be maintained quickly and repeatably. Ability to maintain %e system can maneuver on slightly uneven terrain. traction Antislip %e system ensures that the payload does not slip or fall. Two-year lifetime Product lifetime of at least two years. Cheap %e system is inexpensive compared with foreign competitors. Engineering Characteristics Improvement Direction 2 2 MPa√m n/a N/m N m/sec sec n/a MPa MPa Kg % sec m/sec m m Units Importance Customer Requirements Weight 1 234 5 6 78 9 10 11 12 13 14 15 Factor Shock and scratch 2 91 1 1 resistant Autonomy 4 9 3 9 Payload displacement 3 3 1 9 1 3 1 1 3 Reliability 5 3 9 9 3 9 Safety 5 3 1 9 1 3 9 1 9 9 Easy maintenance 2 1 9 9 3 Ability to mantain 4 93 3 9 1 3 traction Anti-slip 4 1 9 1 1 9 Two year lifetime 2 1 1 1 9 1 Cheap 3 39 3 3 9 3 3 1 Raw Score (932) 50 31 39 71 84 22 86 69 87 61 17 94 79 58 84 Relative Weight % 5.36 3.33 4.18 7.62 9.01 2.36 9.23 7.40 9.33 6.55 1.82 10.09 8.48 6.22 9.01 Rank Order 11 13 12 7 4 14 3 8 2 9 15 1 6 10 4 Figure 2: House of quality of the vehicle. Payload transported to Payload Payload speciﬁed location Payload Whithstand Place payload Maintain traction payload Mechanical energy Electrical Mechanical Electrical energy energy Provide energy energy Transform Steer the system to the system energy Electrical energy Environment Acquire (Analog information) information from the environment Process information Goal position Material Energy Signal Figure 3: Functional representation of the AGV. Journal of Robotics 5 Figure 4: Isometric view of the autonomous guided vehicle. (a) (b) Figure 5: (a) Front and (b) lateral view of the AGV. requirements of some systems and tools that are normally used in an industrial environment. Figures 4 and 5 illustrate the overall design of the AGV platform. %e physical system architecture can be appreciated in the exploded view of the AGV in Figure 6. Starting at the top of the exploded view, there is a lifting platform, followed by the bodywork of the AGV. Next, there is the chassis, and lastly, there is the traction system that includes the sus- pension, the AC electric motors, the gearbox, and the mecanum wheels. 4.1.1. Chassis. %e chassis is the main structure of the AGV and works as a skeleton for the rest of the subsystems. %e suspension is attached to the chassis and the lifting platform structure via mechanical joints; also, it has the necessary spaces to store the electrical components that are part of the Figure 6: Exploded view of the AGV principal subsystems. power and control systems. %is chassis is covered by the bodywork as displayed in Figure 6. %e chassis is made of hot rolled steel, and its diﬀerent 4.1.3. Suspension. %e design of the AGV suspension sections were attached using a welding procedure. An iso- systems consists in a shock absorber designed to reduce metric view of the chassis can be seen in Figure 7. the system vibrations in case the vehicle ﬁnds uneven ground, and this shock absorber is linked to the upper and lower control arms that are attached to the chassis, a 4.1.2. Lifting/Cargo Platform. %e lifting platform is gearbox, and a three-phase electrical motor; the gearbox designed to lift and carry pallets with a maximum weight of and the three-phase motor are joined together using 150 kilogram. %e platform uses a scissor mechanism moved mechanical joints. %e gearbox has a reduction ratio of 1 : by an endless screw that is attached to an electric motor via a 20 and uses a worm drive in order to change the axis of worm drive with a reduction ratio of 1 :10, and this rotation since the mecanum wheel, which is attached to mechanism moves the whole system. Figure 8 shows an the gearbox, has an axis of rotation perpendicular to the isometric view of the mechanism. axis of rotation of the motor. Also, it is important to note 6 Journal of Robotics Figure 7: Isometric view of the AGV chassis. Figure 8: Transport platform. (a) (b) Figure 9: (a) Isometric and (b) exploded view of the suspension system including the three-phase motor, mecanum wheel, and encoder assembly. that the gearbox has an optical encoder assembled, and omnidirectional movements. An isometric and frontal view this encoder is attached to the wheel shaft. %e suspen- of the mecanum wheels are shown in Figure 10. sion system and its components can be seen in Figure 9. As mentioned earlier, the mecanum wheels allow the AGV to perform omnidirectional movements through the combination of diﬀerent spin directions on each wheel; these movements can be seen in Figure 11. Several 4.1.4. Mecanum Wheels. %e AGV prototype uses four Mecanum wheels on a vehicle allows the user to change its mecanum wheels in order to achieve the omnidirectional direction and rotation due to the resultant friction of each mobility required. %ese wheels are composed of a number wheel with the ground. However, the slip generated by of free rolls, with a ± 45 angle rubber cover, that provide these wheels can become one of the main kinematic lateral friction, allowing the AGV to perform problems for vehicle control [29]. Journal of Robotics 7 (a) (b) Figure 10: (a) Isometric and (b) front view of the mecanum wheel. Figure 11: Motions of omnidirectional AGV. 4.2. Vehicle Kinematics. An important step in the design of convenient to know the platform kinematics because with the AGV is the deﬁnition of a proper kinematic model; this is them and using the encoders measurement it is possible to because one of the purposes of the AGV testing platform is estimate the AGV relative position. to be able to navigate autonomously with a navigation al- Figure 12 shows a useful representation to deﬁne the gorithm, which typically requires an estimate of the relative omnidirectional AGV platform kinematics. %e forward and position of the vehicle, and this is also known as the inverse kinematics of the vehicle are given by Taheri and Qiao [37]. odometry of the mobile platform. In this case, it is [r]1 −1 −􏼐l + l 􏼑 x y ⎢ ⎥ 0 ⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎥ v ⎢ ⎥ ⎢ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ x ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ _ ⎥ ⎢ 1 1 􏼐l + l 􏼑 ⎥⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ θ ⎥ ⎢ x y ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ 1 ⎢ ⎥⎢ ⎥ ⎢ 1 ⎥ ⎢ ⎥⎢ ⎥ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ � ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ v ⎥, ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ y ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎢ ⎥ r ⎢ ⎥ ⎢ _ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎥ ⎢ θ ⎥ ⎢ 1 1 −􏼐l + l 􏼑 ⎥ ⎢ ⎥ ⎢ ⎢ 2 ⎥ ⎢ x y ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎣ ⎦ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ω ⎢ ⎥ ⎣ ⎦ z 3 1 −1 􏼐l + l 􏼑 x y (1) [r]1 1 1 1 ⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥⎡ ⎢ ⎤ ⎥ ⎢ ⎥⎢ ⎥ v ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ x ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎡ ⎢ ⎤ ⎥ ⎢ ⎥⎢ _ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ θ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ r ⎥ ⎥ ⎢ ⎥ ⎢ −1 1 1 −1 ⎥⎢ 1 ⎥ ⎢ ⎥ ⎢ ⎢ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ v ⎥ � ⎢ ⎥⎢ ⎥, ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ y ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎣ ⎦ ⎢ ⎥⎢ ⎥ 4 ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ _ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ θ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ 2 ⎥ ⎢ 1 1 1 1 ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎢ ⎥ ⎣ ⎦ z − − l + l l + l l + l l + l θ 􏼐 􏼑 􏼐 􏼑 􏼐 􏼑 􏼐 􏼑 x y x y x y x y 3 8 Journal of Robotics Table 2: Kinematics parameters. i=0 Parameter Value l 43.05 l 57.77 r 10.16 i=2 performs any of the other movements shown in Figure 11 (lateral displacement, forward/backward displacement, or O i=1 diagonal displacement) sequentially. %en, the current po- sitions x and y of the vehicle with respect to the inertial k k frame is given by x � x + Δx cos(θ) − Δy sin(θ), k k−1 R R (3) y � y + Δx sin(θ) + Δy cos(θ), k k−1 R R i=3 where x and y represent the previous positions of the k−1 k−1 vehicle with respect to the inertial frame; and Δx and Δy G x represent the displacements of the vehicle. Figure 12: Vehicle model used for the calculation of inverse and forward kinematics. 4.4. Electrical Design. %e electrical system is made up of a power layer and a control layer. %e power layer uses a three- where v ∈ R corresponds to the forward velocity of the x phase AC electric supply that is connected directly into the vehicle, v ∈ R corresponds to the lateral velocity, ω ∈ R is y z variable frequency drives (VFDs) and then to the three- the angular velocity of the robot around its center, θ with i phase electric motors; this three-phase AC electric supply is i ∈ {0, 1, 2, 3} is the angular velocity of each mecanum wheel, also connected to an AC/DC power supply of 24 V, which is r is the radius of the mecanum wheels, l corresponds to the used to supply 24 V to the control layer components. %e distance from the center of the robot to the center of one of control layer is made up of a programmable logic controller the lateral wheels, and l corresponds to the distance from (PLC) that uses its analog and digital outputs to control the the center of the robot to the center of the front or back speed and spin direction of the motor via the VFD; it also wheels. Table 2 has the values of l , l , and r. x y receives the A and B signals coming from the optical en- coders attached to each wheel, and these signals are read using the high-speed counters (HSCs) in the PLC with a 4.3.PositionEstimation. In order to perform basic testing on sampling frequency of 10 ms. %e PLC is connected via an the AGV prototype and explore its capabilities, it was Ethernet cable to a PC that is used to control the vehicle necessary to implement a basic odometry algorithm to es- using a joystick controller. Figure 13 shows the block dia- timate the global position of the AGV [38, 39]. To do that, gram of the overall system. the ﬁrst step was to calculate the linear velocities of the AGV Table 3 shows the brand and reference of the electrical with the forward kinematics using the angular velocity system main components and their main speciﬁcation or readings from the wheels’ encoders (Figure 12 shows the characteristics. More information about the components can inertial and body frame). %en, the position and orientation be found in their respective manual or datasheet. of the vehicle are given by 4.5. Control System. Initially, an open-loop control system x � 􏽘 v (k)T , R x s was designed because the primary intention of the AGV k�0 testing platform was to test autonomous navigation algo- rithms. %is control system has a programmable logic y � 􏽘 v (k)T , (2) R y s controller (PLC) that receives a setpoint from a PC and then k�0 uses its analog and digital outputs to set a frequency and spin direction in the variable frequency drive (VFD); this VFD θ � 􏽘 ω(k)T , then modulates the three-phase AC signals to set a speciﬁc k�0 speed in the electric motor. where T corresponds to the sampling time for acquiring the encoders’ measurements and calculating the linear velocities. 4.5.1. System Communications. In order to achieve reliable Once the relative movements of the vehicle’s frame were and easy communication between the PLC and the PC, a calculated, the global position of the AGV was calculated as Modbus TCP/IP communication protocol was used, and this follows: between two steps of odometry k − 1 and k, the protocol was based on a client/server model, in which the vehicle ﬁrst rotates and establishes its orientation θ, then it PLC worked as the server and the PC as the client. In Journal of Robotics 9 AC/DC Depth Power Supply Fuse Camera 24V Programmable Circuit Logic Controller Breaker (PLC) PC Joystick External Switch 3 Phase Panel Power Supply Variable Circuit Frequency Liing Motor Breaker Drive (VFD) Platform x5 Mecanum Motor Wheel x4 x4 Encoder Power Layer Control Layer Figure 13: Block diagram of the overall vehicle. Table 3: Electrical components’ general speciﬁcations. Component Reference Specs. Work memory: 75 KB Programmable logic controller (PLC) SIEMENS - SIMATIC S7 - 1200, CPU 1214C dc/dc/dc Supply: 24 V DC High-speed counters (HSCs): 6 1 digital input with galvanic isolation Variable frequency drive (VFD) SIEMENS - SINAMICS G110 3 digital inputs without galvanic isolation 1 analog input AIN: 0–10 V Speed: 1,800 RPM %ree-phase motor SIEMENS - 1LA7 070-4YC60 Power: 0.4 HP Weight: 5 kg Incremental quadrature encoder Resolution: 360 PPR Encoder Autonics - E50S8-360-3-T-24 Supply: 12–24 V Max speed: 5,000 RPM Intel core I5 2.2 GHz PC DELL - LATITUD 3550 RAM: 8 GB OS: Ubuntu 18.04 Use: Indoor/Outdoor Ideal Range: 0.3 to 3 m °° °° Depth camera Intel RealSense D435i FOV: 87 x 58 Depth-out resolution: 1280 × 720 RGB Resolution: 1920 ×1080 Joystick Logitech - EXTREME 3DPRO NA 10 Journal of Robotics (a) (b) Figure 14: (a) Real AGV prototype during assembly and (b) ﬁnal prototype. addition, a joystick was connected to the PC via USB, and were performed in order to validate the design and explore this joystick was used to command the AGV in the desired the AGV capabilities. %is section describes the tests per- directions. formed to the AGV testing prototype and their results. To conﬁgure the Modbus TCP/IP server in the PLC, a static IP address was given to the programming block of the 5.1. Position Estimation Evaluation. %e AGV prototype PLC server; this server was linked with a data block that was tested in all directions of movement shown in Fig- contains a double-word (DWord) array with 16 positions. ure 11. %is test was carried out in order to determine the %e ﬁrst 10 positions are used by the PLC to set the analog average error in the position estimation model in each and digital outputs in order to set the speed and spin di- direction of movement; this error allows a better un- rection of the electric motors. %e remaining 6 positions of derstanding of the AGV’s capabilities when imple- the array are used to store the linear and angular velocities, menting an odometry system based on the encoders’ position, and orientation of the AGV. measurements. To measure this error, the AGV was %e client conﬁgured in the PC was also assigned with a moved in each direction on a concrete ﬂoor, for the linear static IP address; this client was implemented using Python motions the error was recorded when the AGV had 2.7 and its PyModbus library, which was used to write and traveled 2 m in each direction, and each trajectory was read the PLC registers. As mentioned earlier, a joystick was performed 3 times. used to control the AGV and thus was used to set the Table 4 shows the absolute error in cm for each motion in setpoints in the PLC; the reading of this joystick was per- each trajectory and also shows the average error based on the formed using the Pygame library; this library allowed measurements of each trajectory. Table 5 shows the absolute conﬁguring the diﬀerent buttons and controls in the joystick, errors in degrees for the rotational motions, for this test, the allowing to control the AGV in the desired directions. ° ° ° AGV was rotated 90 , 180 , and 360 . As shown in Table 4, the mean absolute error does not surpass 1 cm and the average across all motions is 0.5 cm. On 4.5.2. Software Architecture. %e implementation of the °° the other hand, Table 5 shows a mean average error of 1.07 navigation system requires a correct and reliable integration for the rotational motions. Part of these errors can be caused of external signals within the software to be used. ROS [40] is by some irregularities in the surface in which the robot was open-source software widely used for the development of moved and tire slippage. robotic platforms. We used the navigation stack, which is a meta-package that makes it easy to integrate multiple nodes for autonomous navigation. Two main nodes directly related to the robot’s sensors and actuators were used: the 5.2. Lifting Platform and Loaded Movement. In order to test “odometry source” node and the “base controller” node. %e the lifting platform load requirements, the platform was ﬁrst one was built from (1)−(3), and the readings obtained by loaded with four concrete blocks, each one of 37 kg, the encoders. For the second, an open-loop based controller summing up a total of≈150 kg, and then it was activated script was developed taking into account the joystick. %ese performing several ascension-descension cycles. %is two nodes will be inputs for the future development of the experimental setup can be seen in Figure 15. %is test complete autonomous navigation system. veriﬁed that the lifting platform was able to lift the 150 kg, which was the design requirement; however, the lifting capacity of the platform is greater than 150 kg. 5. Tests and Results To evaluate the AGV’s movement ability while loaded, %e AGV testing prototype was assembled with the designs the AGV performed the motions discussed in Section 5.1 presented in the previous sections. Figure 14 shows the and shown in Figure 11 carrying an approximate weight of prototype during the assembly process and the assembled 150 kg (4 concrete blocks of 37 kg). During the test, the AGV vehicle. Once the prototype was assembled, a series of test performed correctly all the linear and rotational motions. Journal of Robotics 11 Table 4: Linear movement errors in the kinematic model. Trajectory Mean absolute error (cm) Movement 1 2 3 ↑ 0.4 0.6 0.9 0.63 ↓ 0.3 0.7 0.9 0.63 ← 0.5 0.5 0.6 0.53 → 0.4 0.6 0.5 0.50 ↗ 0.5 0.8 1.0 0.77 ↘ 0.1 0 0.1 0.07 ↙ 0.2 0.3 0.6 0.37 ↘ 0.4 0.5 0.5 0.47 Table 5: Rotational movement errors in the kinematic model. Trajectory Mean absolute error (deg) ° ° ° 2–4 Movement 90 180 360 ↺ 0.8 1.2 1.3 1.1 ↻ 0.9 1 1.2 1.03 Figure 15: Lifting platform test. 6. Conclusions and Future Work Data Availability %is document presents the mechanical and electrical %e data that support the ﬁndings of this study are available design of an AGV testing prototype following Dieter’s from the corresponding author, Juan C. Tejada (juan.te- systems engineering methodology. %e prototype was jada@eia.edu.co), upon reasonable request. designed in order to test its capabilities and possible scalability into an industrial platform. During the per- Conflicts of Interest formed tests, it was found that the kinematic model can %e authors declare that they have no conﬂicts of interest. be used to implement an accurate odometry system based on the encoders’ measurements. Section 5.1 shows that the kinematic model error is minimum and can be re- Acknowledgments duced even more with the implementation of a robust %is research was supported by the Universidad EIA (Project control system. %e load tests concluded that the lifting no. CO12020002) and the company SAMCO Ingenierıa. platform fulﬁlled the design requirements of lifting %is research was partially supported by the Universidad de 150 kg; also, the AGV prototype was able to perform all Medell´ın. the required linear and rotational movements carrying the said weight. References In future work, an Intel RealSense D435i depth camera will be integrated in order to implement a simultaneous [1] F. Yao, A. Keller, M. Ahmad, B. Ahmad, R. Harrison, and localization and mapping algorithm using the robotic op- A. W. Colombo, “Optimizing the scheduling of autonomous erating system (ROS) and the open-source RTAB-Map li- guided vehicle in a manufacturing process,” in Proceedings - brary. 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Publisher: Hindawi Publishing Corporation
Copyright: Copyright © 2022 Juan C. Tejada et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ISSN: 1687-9600
eISSN: 1687-9619
DOI: 10.1155/2022/7712312
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Abstract

Hindawi Journal of Robotics Volume 2022, Article ID 7712312, 13 pages https://doi.org/10.1155/2022/7712312 Research Article A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype 1 1 1 Juan C. Tejada , Alejandro Toro-Ossaba , Santiago Muñoz Montoya , and Santiago Ru ´ a Faculty of Engineering Department of Mechatronics, Universidad EIA Envigado, Medell´ın, Colombia Electronics and Telecommunications Engineering Department, Universidad de Medell´ın, Medell´ın, Colombia Correspondence should be addressed to Juan C. Tejada; juan.tejada@eia.edu.co Received 5 January 2022; Accepted 25 February 2022; Published 20 March 2022 Academic Editor: L. Fortuna Copyright © 2022 Juan C. Tejada et al. %is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. %is paper addresses the mechanical and electrical design of an autonomous guided vehicle (AGV) test prototype based on a systems engineering approach. First, the diﬀerent phases of the systems engineering approach are described. %e conceptual design begins with the house of quality, which weighs the relevance of each user requirement and ends with a functional representation of the vehicle. %en, the mechanical and electrical design are presented considering diﬀerent subsystems such as the chassis, cargo platform, suspension system, power, and control components. Finally, diﬀerent tests were carried out on the prototype, validating its movement and load capacities. %e systems engineering approach as a methodology for the construction of complex systems has proven to be an excellent tool for the development of autonomous guided vehicles. technologies such as mobile robots [9]. %ese robots can 1. Introduction perform diﬀerent movements and tasks within industrial Nowadays, smart manufacturing is the evolution from environments, allowing greater ﬂexibility and scalability in traditional factories to fully connected, ﬂexible, and diﬀerent processes [10, 11]. reconﬁgurable systems that can easily adapt to frequently Mobile robots can be divided into three categories [12] changing product and production requirements [1]. %is according to their moving mechanism: wheeled [13–15], ﬂexible manufacturing oﬀers greater capacity to produce legged [16–18], or hybrid [19, 20]. Wheeled robots, and in goods on a modular system, rather than the traditional linear particular autonomous guided vehicles (AGVs), are widely one [2], allowing to select which processes or tasks are used in industrial environments due to their simplicity and performed without the need of reconﬁguring the whole few actuators, making them a very important component of smart factories and smart logistics [21]. process [3]. Over the past decades, ﬂexibility has become one of the Regarding the development and manufacturing of AGVs determinant factors in logistics and production system in the last ten years, Peng and others [22] designed a material design, particularly Industry 4.0 as been identiﬁed has a conveying mobile robots with a four-wheel driven chassis determinant factor in the evolution of ﬂexible and omnidirectional mobility. Li and others [23] proposed manufacturing, bringing emerging technologies that allow diﬀerent mecanum wheel conﬁgurations for omnidirec- the decentralization and ﬂexibility needed to transform the tional mobile robots based on topological design methods. traditional production environment [4–8]. %is emergence Tamara and others [24] proposed a new low-cost electronic of Industry 4.0, smart manufacturing, ﬂexible systems, and system for an AGV type forklift. Zhang and Henke [25] built logistics has also motivated the development of new a new AGV based on a mechatronic development cycle 2 Journal of Robotics accounting for user requirements, modeling, synthesis, allows to map the user’s needs into a ﬁnal product [36]. among other phases. Aloui and others [26] developed a Figure 1 presents the steps of such methodology. design methodology for AGVs with two phases: a top-down %is research was only developed until the initial stages phase containing user requirements, functional description, of the testing and reﬁnement phase; this is because the aim and structural modeling; and a bottom-up phase for the was to develop a working prototype. Future work will focus integration and implementation of the models. on the reﬁnement stage. Nowadays, many of the technologies start with the idea of building a complex system or having the ﬁnal solution 2.1. Phase 0: Planning. %e planning phase is an essential rather than having a clear problem deﬁned [27]. It is im- part of the product design life cycle. In this stage, an in- portant to have a methodology that allows mapping the vestigation and scoping of the product is carried out; this needs of interested parties in functional requirements, which investigation normally includes searching for the state of the serves as the basis for the construction of a viable techno- art related to the topic, the potential market for the product, logical solution [28]. To use a clear methodology for complex a ﬁnancial analysis for the next phases, and the product systems allows you to have a track record of the decisions, beneﬁts and possible issues. %e idea of this vehicle arises even when the result of the system is not as expected or has from the need to generate appropriation of knowledge in the imperfections [29]. Systems engineering is a multidisci- construction of autonomous vehicles to impact the plinary approach to the design, manufacture, operation, and Colombian robotic industry with the development and retirement of a complex system such as an autonomous commercialization of new kinds of AGV robotic systems for vehicle [30], aircrafts [31], manufacturing automation [32], industrial environments. and other kinds of machines [33]. For instance, Aristizabal and others [34] presented a modular hardware architecture for an ROV based on systems engineering. Sadraey [31] 2.2. Phase 1 and Phase 2: Concept Development and System- provides a guide for aircraft design based on an engineering Level Design. Phase 1 and phase 2 are generally addressed system considering diﬀerent systems such as wing, tail, and together and correspond to the conceptual design stage. propulsion. Tagliaferri and others [35] proposed an evalu- Phase 1, known as concept development, considers the ation of the life cycle of electric and hybrid vehicles based on diﬀerent ways the product and each subsystem can be a systems engineering approach. designed [36]; this phase generally takes what was learned %is research presents the mechanical, electrical, and during the planning phase and also new data acquired from software development of an omnidirectional autonomous surveys, focus groups, benchmarking, and the quality guided vehicle (AGV) testing prototype, which will be used function deployment (QFD); a common tool used in this in future work for the implementation and testing of au- phase is the house of quality (HoQ), which allows to deﬁne tonomous navigation algorithms using robot operating the priority of the user requirements and engineering system (ROS) to validate its scalability in an industrial characteristics of the product. Section 3.1 presents the QFD environment. %e main contribution of this research is the and an overview of the concept development. use of systems engineering as a methodology or tool in the Phase 2, known as the system-level design, is where the development of an autonomous guided vehicle for the in- functions of the product are examined, leading to the di- dustry. %is AGV was developed to reduce the develop- vision of the product into various subsystems [36]. In this mental gap of mobile robots applied to the industry in phase, all the subsystems are deﬁned and arranged into a Colombia. %e organization of the paper is as follows: product architecture, and also the interfaces between sub- Section 2 presents the methodology used in the mechanical, systems are deﬁned. %is is the phase where the product or electrical, and software development of the vehicle; Section 3 prototype begins to take shape. %is phase is addressed in describes the conceptual design of the vehicle taking into Section 3.2. account stakeholder requirements; Section 4 presents the mechanical, electrical, and software design of the vehicle; 2.3. Phase 3: Detail Design. Phase 3, known as detail design, Section 5 contains some tests and results carried out in the is where the design is brought to the state of a complete AGV; and Section 6 presents some conclusions and future engineering description of a tested and producible product directions for the AGV. [36]. In this stage, all the subsystems proposed in phase 2 are designed in detail in order to meet the user requirements 2. Systems Engineering Methodology deﬁned in phase 1. In the case of this research, this phase includes the detail mechanical design of the AGV prototype An autonomous guided vehicle (AGV) is a complex system; in Section 4.1; the vehicle kinematics and position estimation therefore, every part of its design must be planned in detail. algorithm in Sections 4.2 and 4.3, respectively; the detailed A roadmap allows for a clear understanding of the system electrical design in Section 4.4; and the control system life cycle and a ﬁnal product that meets deﬁned user re- implemented in the vehicle in Section 4.5. quirements. To do this, a series of design stages must be performed, beginning with general planning, followed by concept development, system-level and detail design, test- 2.4. Phase 4: Testing and Reﬁnement. %e last phase addressed in this research is phase 4, known as testing and ing, reﬁnement, and the production ramp-up. %e systems engineering approach to the design of complex systems reﬁnement; this phase consists in testing the developed Journal of Robotics 3 Phase 1 Phase 2 Phase 4 Phase 5 Phase 0 Phase 3 Concept System-level Testing and Production Planning Detail Design Development Design Refinement Ramp-up Figure 1: Product development process [36]. prototype in order to verify that it fulﬁlls the user re- (3) Rigidity of suspension springs quirements deﬁned in phase 1. Once the prototype is tested, (4) Motor torque the results are reviewed to determine if the prototype is ready (5) Vehicle speed for production or whether it is necessary to perform further (6) Assembly and disassembly time reﬁnement prior to production. As mentioned earlier that the scope of this research ended in the testing phase of the (7) Degrees of freedom prototype, future work will address the reﬁnement stage on (8) Adhesion of the payload contact area phase 4 and will increase the scalability of the vehicle, closing (9) Wear resistance the gap between a testing prototype and an industrial (10) Vehicle size product. %e testing performed on the AGV prototype along with the results of those tests can be found in Section 5. (11) Probability of blocking (12) Braking time when detecting an obstacle 3. Conceptual Design (13) Vehicle acceleration (14) Payload contact area %is section presents both the concept development and the system-level design of the AGV prototype. It covers the (15) Accuracy in estimating position within the facilities analysis of the user requirements and engineering charac- With the requirements and the characteristics identiﬁed, teristics using the house of quality (HoQ) tool and the it is now possible to implement the house of quality (HoQ) system-level design in which all the AGV subsystems are presented in Figure 2. depicted in a functional representation. 3.2. System-Level Design. After having the appropriate en- 3.1. Quality Function Deployment (QFD). %e QFD is a tool gineering characteristics in mind, the next step is to make a used by a wide variety of companies to design a product functional representation of the vehicle that is going to be based on the requirements of its users; this tool generates an made. Systematic design is a method that provides a way to understanding of the problem and common terms for the describe a system or product in a general form based on its entire work team, helping in the generation of concepts and main functions, in which each subsystem is taken as a box the selection of the engineering characteristics that best meet that transforms energy, material, and signals to obtain the the needs of customers and stakeholders. %e QFD consists desired output [36]. Figure 3 presents the functional rep- of several phases throughout the development of the resentation of the AGV prototype that describes the main product; this investigation only carried out initial one, which functions of the system. corresponds to the HoQ following the methodology used by With the functional representation, several concepts U.S. companies [36]. were presented and discussed to address each one of the functions required for the system. %e concept selection was 3.1.1. House of Quality (HoQ). %ere are many ways to made using a selection matrix following Dieter’s method- design an HoQ as it has diﬀerent rooms, each with a par- ology [36]. An evaluation of how much the proposed ticular function. %e principal rooms for this research were concepts fulﬁlled the engineering characteristics and user those corresponding to user requirements and engineering requirements was realized, and the selected concept was the characteristics, which were analyzed through the relation- one with greater score among those proposed. ship matrix, resulting in the importance ranking to consider in the design phase. Table 1 speciﬁes each of the customer 4. Detail Design requirements and its description. %ese requirements are based upon past experiences of %is section presents the detail design of the subsystems the previous products and the stakeholders’ needs for future proposed in the conceptual design. First, the mechanical developments. For the next step, it is important to translate design is presented along with the kinematic model of the these needs into measurable values, and this was accom- vehicle and the proposed position estimation algorithm. plished by reviewing the competitor’s characteristics and Finally, the electrical design is presented along with the analyzing other factors that could intervene in the devel- proposed control system. opment process; the following list enumerates the ones chosen: 4.1. Mechanical Design. %e AGV was conceived as a testing (1) Rigidity of the shell material prototype with the purpose of validating its capabilities as an (2) Number of tools required for maintenance industrial platform. %e system includes in its design 4 Journal of Robotics Table 1: Customer requirements. Requirement Description Shock and scratch %e system is resistant to shocks and scratches that can be caused in normal factory operation. resistant %e system can be moved anywhere in the facility without the need for modiﬁcations or installation of auxiliary Autonomy systems. Payload displacement %e system can move a payload of up to 150 kg. Reliability %e system can recover automatically after detecting an obstacle. Safety %e system is safe to work together with the operators. Easy maintenance %e system can be maintained quickly and repeatably. Ability to maintain %e system can maneuver on slightly uneven terrain. traction Antislip %e system ensures that the payload does not slip or fall. Two-year lifetime Product lifetime of at least two years. Cheap %e system is inexpensive compared with foreign competitors. Engineering Characteristics Improvement Direction 2 2 MPa√m n/a N/m N m/sec sec n/a MPa MPa Kg % sec m/sec m m Units Importance Customer Requirements Weight 1 234 5 6 78 9 10 11 12 13 14 15 Factor Shock and scratch 2 91 1 1 resistant Autonomy 4 9 3 9 Payload displacement 3 3 1 9 1 3 1 1 3 Reliability 5 3 9 9 3 9 Safety 5 3 1 9 1 3 9 1 9 9 Easy maintenance 2 1 9 9 3 Ability to mantain 4 93 3 9 1 3 traction Anti-slip 4 1 9 1 1 9 Two year lifetime 2 1 1 1 9 1 Cheap 3 39 3 3 9 3 3 1 Raw Score (932) 50 31 39 71 84 22 86 69 87 61 17 94 79 58 84 Relative Weight % 5.36 3.33 4.18 7.62 9.01 2.36 9.23 7.40 9.33 6.55 1.82 10.09 8.48 6.22 9.01 Rank Order 11 13 12 7 4 14 3 8 2 9 15 1 6 10 4 Figure 2: House of quality of the vehicle. Payload transported to Payload Payload speciﬁed location Payload Whithstand Place payload Maintain traction payload Mechanical energy Electrical Mechanical Electrical energy energy Provide energy energy Transform Steer the system to the system energy Electrical energy Environment Acquire (Analog information) information from the environment Process information Goal position Material Energy Signal Figure 3: Functional representation of the AGV. Journal of Robotics 5 Figure 4: Isometric view of the autonomous guided vehicle. (a) (b) Figure 5: (a) Front and (b) lateral view of the AGV. requirements of some systems and tools that are normally used in an industrial environment. Figures 4 and 5 illustrate the overall design of the AGV platform. %e physical system architecture can be appreciated in the exploded view of the AGV in Figure 6. Starting at the top of the exploded view, there is a lifting platform, followed by the bodywork of the AGV. Next, there is the chassis, and lastly, there is the traction system that includes the sus- pension, the AC electric motors, the gearbox, and the mecanum wheels. 4.1.1. Chassis. %e chassis is the main structure of the AGV and works as a skeleton for the rest of the subsystems. %e suspension is attached to the chassis and the lifting platform structure via mechanical joints; also, it has the necessary spaces to store the electrical components that are part of the Figure 6: Exploded view of the AGV principal subsystems. power and control systems. %is chassis is covered by the bodywork as displayed in Figure 6. %e chassis is made of hot rolled steel, and its diﬀerent 4.1.3. Suspension. %e design of the AGV suspension sections were attached using a welding procedure. An iso- systems consists in a shock absorber designed to reduce metric view of the chassis can be seen in Figure 7. the system vibrations in case the vehicle ﬁnds uneven ground, and this shock absorber is linked to the upper and lower control arms that are attached to the chassis, a 4.1.2. Lifting/Cargo Platform. %e lifting platform is gearbox, and a three-phase electrical motor; the gearbox designed to lift and carry pallets with a maximum weight of and the three-phase motor are joined together using 150 kilogram. %e platform uses a scissor mechanism moved mechanical joints. %e gearbox has a reduction ratio of 1 : by an endless screw that is attached to an electric motor via a 20 and uses a worm drive in order to change the axis of worm drive with a reduction ratio of 1 :10, and this rotation since the mecanum wheel, which is attached to mechanism moves the whole system. Figure 8 shows an the gearbox, has an axis of rotation perpendicular to the isometric view of the mechanism. axis of rotation of the motor. Also, it is important to note 6 Journal of Robotics Figure 7: Isometric view of the AGV chassis. Figure 8: Transport platform. (a) (b) Figure 9: (a) Isometric and (b) exploded view of the suspension system including the three-phase motor, mecanum wheel, and encoder assembly. that the gearbox has an optical encoder assembled, and omnidirectional movements. An isometric and frontal view this encoder is attached to the wheel shaft. %e suspen- of the mecanum wheels are shown in Figure 10. sion system and its components can be seen in Figure 9. As mentioned earlier, the mecanum wheels allow the AGV to perform omnidirectional movements through the combination of diﬀerent spin directions on each wheel; these movements can be seen in Figure 11. Several 4.1.4. Mecanum Wheels. %e AGV prototype uses four Mecanum wheels on a vehicle allows the user to change its mecanum wheels in order to achieve the omnidirectional direction and rotation due to the resultant friction of each mobility required. %ese wheels are composed of a number wheel with the ground. However, the slip generated by of free rolls, with a ± 45 angle rubber cover, that provide these wheels can become one of the main kinematic lateral friction, allowing the AGV to perform problems for vehicle control [29]. Journal of Robotics 7 (a) (b) Figure 10: (a) Isometric and (b) front view of the mecanum wheel. Figure 11: Motions of omnidirectional AGV. 4.2. Vehicle Kinematics. An important step in the design of convenient to know the platform kinematics because with the AGV is the deﬁnition of a proper kinematic model; this is them and using the encoders measurement it is possible to because one of the purposes of the AGV testing platform is estimate the AGV relative position. to be able to navigate autonomously with a navigation al- Figure 12 shows a useful representation to deﬁne the gorithm, which typically requires an estimate of the relative omnidirectional AGV platform kinematics. %e forward and position of the vehicle, and this is also known as the inverse kinematics of the vehicle are given by Taheri and Qiao [37]. odometry of the mobile platform. In this case, it is [r]1 −1 −􏼐l + l 􏼑 x y ⎢ ⎥ 0 ⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎥ v ⎢ ⎥ ⎢ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ x ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ _ ⎥ ⎢ 1 1 􏼐l + l 􏼑 ⎥⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ θ ⎥ ⎢ x y ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ 1 ⎢ ⎥⎢ ⎥ ⎢ 1 ⎥ ⎢ ⎥⎢ ⎥ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ � ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ v ⎥, ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ y ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎢ ⎥ r ⎢ ⎥ ⎢ _ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎥ ⎢ θ ⎥ ⎢ 1 1 −􏼐l + l 􏼑 ⎥ ⎢ ⎥ ⎢ ⎢ 2 ⎥ ⎢ x y ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎣ ⎦ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ω ⎢ ⎥ ⎣ ⎦ z 3 1 −1 􏼐l + l 􏼑 x y (1) [r]1 1 1 1 ⎡ ⎢ ⎤ ⎥ ⎢ ⎥ ⎢ ⎥⎡ ⎢ ⎤ ⎥ ⎢ ⎥⎢ ⎥ v ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ x ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎡ ⎢ ⎤ ⎥ ⎢ ⎥⎢ _ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ θ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ r ⎥ ⎥ ⎢ ⎥ ⎢ −1 1 1 −1 ⎥⎢ 1 ⎥ ⎢ ⎥ ⎢ ⎢ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ v ⎥ � ⎢ ⎥⎢ ⎥, ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ y ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎣ ⎦ ⎢ ⎥⎢ ⎥ 4 ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ _ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ θ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ 2 ⎥ ⎢ 1 1 1 1 ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎢ ⎥ ⎣ ⎦ z − − l + l l + l l + l l + l θ 􏼐 􏼑 􏼐 􏼑 􏼐 􏼑 􏼐 􏼑 x y x y x y x y 3 8 Journal of Robotics Table 2: Kinematics parameters. i=0 Parameter Value l 43.05 l 57.77 r 10.16 i=2 performs any of the other movements shown in Figure 11 (lateral displacement, forward/backward displacement, or O i=1 diagonal displacement) sequentially. %en, the current po- sitions x and y of the vehicle with respect to the inertial k k frame is given by x � x + Δx cos(θ) − Δy sin(θ), k k−1 R R (3) y � y + Δx sin(θ) + Δy cos(θ), k k−1 R R i=3 where x and y represent the previous positions of the k−1 k−1 vehicle with respect to the inertial frame; and Δx and Δy G x represent the displacements of the vehicle. Figure 12: Vehicle model used for the calculation of inverse and forward kinematics. 4.4. Electrical Design. %e electrical system is made up of a power layer and a control layer. %e power layer uses a three- where v ∈ R corresponds to the forward velocity of the x phase AC electric supply that is connected directly into the vehicle, v ∈ R corresponds to the lateral velocity, ω ∈ R is y z variable frequency drives (VFDs) and then to the three- the angular velocity of the robot around its center, θ with i phase electric motors; this three-phase AC electric supply is i ∈ {0, 1, 2, 3} is the angular velocity of each mecanum wheel, also connected to an AC/DC power supply of 24 V, which is r is the radius of the mecanum wheels, l corresponds to the used to supply 24 V to the control layer components. %e distance from the center of the robot to the center of one of control layer is made up of a programmable logic controller the lateral wheels, and l corresponds to the distance from (PLC) that uses its analog and digital outputs to control the the center of the robot to the center of the front or back speed and spin direction of the motor via the VFD; it also wheels. Table 2 has the values of l , l , and r. x y receives the A and B signals coming from the optical en- coders attached to each wheel, and these signals are read using the high-speed counters (HSCs) in the PLC with a 4.3.PositionEstimation. In order to perform basic testing on sampling frequency of 10 ms. %e PLC is connected via an the AGV prototype and explore its capabilities, it was Ethernet cable to a PC that is used to control the vehicle necessary to implement a basic odometry algorithm to es- using a joystick controller. Figure 13 shows the block dia- timate the global position of the AGV [38, 39]. To do that, gram of the overall system. the ﬁrst step was to calculate the linear velocities of the AGV Table 3 shows the brand and reference of the electrical with the forward kinematics using the angular velocity system main components and their main speciﬁcation or readings from the wheels’ encoders (Figure 12 shows the characteristics. More information about the components can inertial and body frame). %en, the position and orientation be found in their respective manual or datasheet. of the vehicle are given by 4.5. Control System. Initially, an open-loop control system x � 􏽘 v (k)T , R x s was designed because the primary intention of the AGV k�0 testing platform was to test autonomous navigation algo- rithms. %is control system has a programmable logic y � 􏽘 v (k)T , (2) R y s controller (PLC) that receives a setpoint from a PC and then k�0 uses its analog and digital outputs to set a frequency and spin direction in the variable frequency drive (VFD); this VFD θ � 􏽘 ω(k)T , then modulates the three-phase AC signals to set a speciﬁc k�0 speed in the electric motor. where T corresponds to the sampling time for acquiring the encoders’ measurements and calculating the linear velocities. 4.5.1. System Communications. In order to achieve reliable Once the relative movements of the vehicle’s frame were and easy communication between the PLC and the PC, a calculated, the global position of the AGV was calculated as Modbus TCP/IP communication protocol was used, and this follows: between two steps of odometry k − 1 and k, the protocol was based on a client/server model, in which the vehicle ﬁrst rotates and establishes its orientation θ, then it PLC worked as the server and the PC as the client. In Journal of Robotics 9 AC/DC Depth Power Supply Fuse Camera 24V Programmable Circuit Logic Controller Breaker (PLC) PC Joystick External Switch 3 Phase Panel Power Supply Variable Circuit Frequency Liing Motor Breaker Drive (VFD) Platform x5 Mecanum Motor Wheel x4 x4 Encoder Power Layer Control Layer Figure 13: Block diagram of the overall vehicle. Table 3: Electrical components’ general speciﬁcations. Component Reference Specs. Work memory: 75 KB Programmable logic controller (PLC) SIEMENS - SIMATIC S7 - 1200, CPU 1214C dc/dc/dc Supply: 24 V DC High-speed counters (HSCs): 6 1 digital input with galvanic isolation Variable frequency drive (VFD) SIEMENS - SINAMICS G110 3 digital inputs without galvanic isolation 1 analog input AIN: 0–10 V Speed: 1,800 RPM %ree-phase motor SIEMENS - 1LA7 070-4YC60 Power: 0.4 HP Weight: 5 kg Incremental quadrature encoder Resolution: 360 PPR Encoder Autonics - E50S8-360-3-T-24 Supply: 12–24 V Max speed: 5,000 RPM Intel core I5 2.2 GHz PC DELL - LATITUD 3550 RAM: 8 GB OS: Ubuntu 18.04 Use: Indoor/Outdoor Ideal Range: 0.3 to 3 m °° °° Depth camera Intel RealSense D435i FOV: 87 x 58 Depth-out resolution: 1280 × 720 RGB Resolution: 1920 ×1080 Joystick Logitech - EXTREME 3DPRO NA 10 Journal of Robotics (a) (b) Figure 14: (a) Real AGV prototype during assembly and (b) ﬁnal prototype. addition, a joystick was connected to the PC via USB, and were performed in order to validate the design and explore this joystick was used to command the AGV in the desired the AGV capabilities. %is section describes the tests per- directions. formed to the AGV testing prototype and their results. To conﬁgure the Modbus TCP/IP server in the PLC, a static IP address was given to the programming block of the 5.1. Position Estimation Evaluation. %e AGV prototype PLC server; this server was linked with a data block that was tested in all directions of movement shown in Fig- contains a double-word (DWord) array with 16 positions. ure 11. %is test was carried out in order to determine the %e ﬁrst 10 positions are used by the PLC to set the analog average error in the position estimation model in each and digital outputs in order to set the speed and spin di- direction of movement; this error allows a better un- rection of the electric motors. %e remaining 6 positions of derstanding of the AGV’s capabilities when imple- the array are used to store the linear and angular velocities, menting an odometry system based on the encoders’ position, and orientation of the AGV. measurements. To measure this error, the AGV was %e client conﬁgured in the PC was also assigned with a moved in each direction on a concrete ﬂoor, for the linear static IP address; this client was implemented using Python motions the error was recorded when the AGV had 2.7 and its PyModbus library, which was used to write and traveled 2 m in each direction, and each trajectory was read the PLC registers. As mentioned earlier, a joystick was performed 3 times. used to control the AGV and thus was used to set the Table 4 shows the absolute error in cm for each motion in setpoints in the PLC; the reading of this joystick was per- each trajectory and also shows the average error based on the formed using the Pygame library; this library allowed measurements of each trajectory. Table 5 shows the absolute conﬁguring the diﬀerent buttons and controls in the joystick, errors in degrees for the rotational motions, for this test, the allowing to control the AGV in the desired directions. ° ° ° AGV was rotated 90 , 180 , and 360 . As shown in Table 4, the mean absolute error does not surpass 1 cm and the average across all motions is 0.5 cm. On 4.5.2. Software Architecture. %e implementation of the °° the other hand, Table 5 shows a mean average error of 1.07 navigation system requires a correct and reliable integration for the rotational motions. Part of these errors can be caused of external signals within the software to be used. ROS [40] is by some irregularities in the surface in which the robot was open-source software widely used for the development of moved and tire slippage. robotic platforms. We used the navigation stack, which is a meta-package that makes it easy to integrate multiple nodes for autonomous navigation. Two main nodes directly related to the robot’s sensors and actuators were used: the 5.2. Lifting Platform and Loaded Movement. In order to test “odometry source” node and the “base controller” node. %e the lifting platform load requirements, the platform was ﬁrst one was built from (1)−(3), and the readings obtained by loaded with four concrete blocks, each one of 37 kg, the encoders. For the second, an open-loop based controller summing up a total of≈150 kg, and then it was activated script was developed taking into account the joystick. %ese performing several ascension-descension cycles. %is two nodes will be inputs for the future development of the experimental setup can be seen in Figure 15. %is test complete autonomous navigation system. veriﬁed that the lifting platform was able to lift the 150 kg, which was the design requirement; however, the lifting capacity of the platform is greater than 150 kg. 5. Tests and Results To evaluate the AGV’s movement ability while loaded, %e AGV testing prototype was assembled with the designs the AGV performed the motions discussed in Section 5.1 presented in the previous sections. Figure 14 shows the and shown in Figure 11 carrying an approximate weight of prototype during the assembly process and the assembled 150 kg (4 concrete blocks of 37 kg). During the test, the AGV vehicle. Once the prototype was assembled, a series of test performed correctly all the linear and rotational motions. Journal of Robotics 11 Table 4: Linear movement errors in the kinematic model. Trajectory Mean absolute error (cm) Movement 1 2 3 ↑ 0.4 0.6 0.9 0.63 ↓ 0.3 0.7 0.9 0.63 ← 0.5 0.5 0.6 0.53 → 0.4 0.6 0.5 0.50 ↗ 0.5 0.8 1.0 0.77 ↘ 0.1 0 0.1 0.07 ↙ 0.2 0.3 0.6 0.37 ↘ 0.4 0.5 0.5 0.47 Table 5: Rotational movement errors in the kinematic model. Trajectory Mean absolute error (deg) ° ° ° 2–4 Movement 90 180 360 ↺ 0.8 1.2 1.3 1.1 ↻ 0.9 1 1.2 1.03 Figure 15: Lifting platform test. 6. Conclusions and Future Work Data Availability %is document presents the mechanical and electrical %e data that support the ﬁndings of this study are available design of an AGV testing prototype following Dieter’s from the corresponding author, Juan C. Tejada (juan.te- systems engineering methodology. %e prototype was jada@eia.edu.co), upon reasonable request. designed in order to test its capabilities and possible scalability into an industrial platform. During the per- Conflicts of Interest formed tests, it was found that the kinematic model can %e authors declare that they have no conﬂicts of interest. be used to implement an accurate odometry system based on the encoders’ measurements. 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Journal

Journal of Robotics – Hindawi Publishing Corporation

Published: Mar 21, 2022

References

Optimizing the scheduling of autonomous guided vehicle in a manufacturing process,

F. Yao, A. Keller, M. Ahmad, B. Ahmad, R. Harrison, and A. W. Colombo
Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal,

Y. Liao, F. Deschamps, E. d. F. R. Loures, and L. F. P. Ramos
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L. Lynch, F. McGuinness, J. Clifford et al.
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A. Das
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R. Dubey and S. S. Ali
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A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype

A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype

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A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype

A Systems Engineering Approach for the Design of an Omnidirectional Autonomous Guided Vehicle (AGV) Testing Prototype

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