Scientia Iranica B (2020) 27(1), 330{340 Sharif University of Technology Scientia Iranica Transactions B: Mechanical Engineering http://scientiairanica.sharif.edu Modeling, control, and simulation of a SCARA PRR-type robot manipulator M.E. Uk, F.B. Sajjad Ali Shah, M. Soyaslan, and O. Eldogan Faculty of Technology, Department of Mechatronics Engineering, Sakarya University, Sakarya, Turkey. Received 19 June 2018; received in revised form 2 September 2018; accepted 29 October 2018 KEYWORDS Abstract. In this study, a SCARA Prismatic-Revolute-Revolute-type (PRR) robot manipulator is designed and implemented. Firstly, the SCARA robot is designed in SCARA robot; accordance with the mechanical calculations. Then, forward and inverse kinematic Real-time control; equations of the robot are derived by using D-H parameters and analytical methods. The Modelling; software is developed according to the obtained Cartesian velocities from joint velocities Simulation; and joint velocities from Cartesian velocities. The trajectory planning is designed using Prismatic-Revolute- the calculated kinematic equations, and the simulation is performed in MATLAB VRML Revolute (PRR); environment. A stepping motor is used for the prismatic joint of the robot, and servo Servo motor. motors are used for revolute joints. While most of the SCARA robot studies focus on the Revolute-Revolute-Prismatic -type (RRP) servo control strategy, this work focuses on PRR-type and both stepper and servo control structures. The objects in the desired points of the workspace are picked and placed to another desired point synchronously with the simulation. Therefore, the performance of the robot is examined experimentally. © 2020 Sharif University of Technology. All rights reserved. 1. Introduction can operate without the need for large areas. For this reason, the processes such as packaging, sorting, Nowadays, the objective of production at high speeds alignment, planar welding, and assembly in the pro- with low costs and low error rates in industrial pro- duction lines are usually performed with SCARA-type duction lines has gained great importance in terms of manipulators. The rst SCARA robot was developed competitiveness. For this reason, companies often use in 1978 by Professor Hiroshi Makino at Yamanashi di erent types of robots, such as Cartesian, SCARA, University in Japan [3]. Afterwards, many types etc., in industrial applications. Cartesian systems are of SCARA robots have emerged to be used in the widely used in high-density warehouses and, generally, machine, automotive, and robot industries. have both shuttle and aisle robots that generate the In literature studies, kinematic and dynamic Cartesian structure [1,2]. SCARA (Selective Compli- modeling, simulation analysis, di erent control meth- ance Assembly Robot Arm) manipulators take up less ods, and trajectory planning have been studied both space than Cartesian systems, are easier to install, and theoretically and experimentally. Di erent decentral- ized and centralized (model-based) controllers have *. Corresponding author. Tel.: +90 2642956912; been tested with experimental studies of an industrial Fax: +90 2642956424 SCARA robot. E-mail addresses: [email protected] (M.E. As a result, the performance of decentralized Uk); [email protected] (F.B. Sajjad Ali Shah); [email protected] (M. Soyaslan); controllers was found to be suciently accurate for a [email protected] (O. Eldogan) large number of industrial applications [4]. Accurate results of experimental studies depend on well-made doi: 10.24200/sci.2018.51214.2065 mathematical modeling. In SCARA robots, which M.E. Uk et al./Scientia Iranica, Transactions B: Mechanical Engineering 27 (2020) 330{340 331 are generally used in industrial applications, it is heavy weights is a challenge. Since the base is xed very important to make both dynamic and kinematic on one point, powerful torque motors for lifting heavy calculations accurately in order to make the system loads linearly can be used easily. work properly. While Das and Dulger [5] developed a In this study, a PRR-type (Prismatic-Revolute- complete mathematical model with actuator dynamics Revolute) SCARA robot manipulator is designed. In and motion equations derived by using the Lagrangian addition, a gripper is placed on the last joint so that mechanics, Alshamasin et al. [6] investigated kinematic the objects can be picked and placed at the desired modeling and simulation of a SCARA robot by using locations. In the rst section, the usage areas of solid dynamics by means of Matlab/Simulink. Unlike SCARA robots and the studies in the literature are other studies, Urrea and Kern [7] implemented a mentioned. In Section 2, the forward kinematics of the simulation of a 5-Degree-Of-Freedom (DOF) SCARA robot is obtained by using the Denavit-Hartenberg (D- manipulator using Matlab/Simulink software. Their H) method [22]. Then, the inverse kinematic equations study has no physical application, although it bears and Jacobian matrix are obtained by using analytical similarity with the work we have done. This study methods. In Section 3, the experimental setup of enjoys some advantages over these types of works, the robot is explained. In Section 4, the control and which include only modeling and simulation. Kaleli simulation software are described. In the conclusion et al. [8] and Korayem et al. [9] designed a program section, the results and discussion are presented. for simulating and animating the robot kinematics and dynamics in LabView software. Similar to these 2. Robot kinematics works, there are various robot control, simulation, and calculation program studies in the literature [10{20]. 2.1. Forward kinematics While some of them are just based on the analysis and Robot forward kinematics deals with the relationship simulation of one type of robot arms, some give results among the positions, velocities, and accelerations of for robots in di erent types. robot joints [23]. A robot consists of links that are SCARA robots with RRP (Revolute-Revolute- attached to each other by prismatic or rotary joints. Prismatic) or PRR (Prismatic-Revolute-Revolute) Coordinate systems are placed to each joint to nd the joint con gurations are easy to provide linear move- transformation matrices that set the relation between ment in vertical directions. RRP and PRR types two neighboring joints. The transformation matrix have some advantages and disadvantages. RRP-type i1 between the two joints is shown like iT . The relation SCARA manipulators are very common in light-duty between the base frame and the tool frame is de ned by applications that require precision and speed, which is the serial joint transformation matrices. This relation dicult to achieve by human beings [21]. While the is called forward kinematics and shown in Eq. (1): prismatic joint motor is only lifting the objects in RRP type, it is lifting the whole robot structure with the 0 T = 0T 1T 2T 3T N1T: (1) objects in PRR type. Therefore, the prismatic joint N 1 2 3 4 N motor of PRR type has higher torque than that of The projected SCARA robot and the axes on RRP type. Therefore, the PRR-type SCARA robot the joints are shown in Figure 1. While d3 is the con guration is preferred in applications, where lifting length of the vertical joint, l1 and l2 are the horizontal Figure 1. Joint axes and implemented SCARA robot. 332 M.E. Uk et al./Scientia Iranica, Transactions B: Mechanical Engineering 27 (2020) 330{340 2 3 2 3 Table 1. D H parameters. c1l1 + c12l2 P1 6 7 6 7 a b c d s1l1 + s12l2 P2 i i1 ai1 i di O = P = 6 7 = 6 7 : (4) 4 d3 5 4P35 1 0 0 0 d3 1 1 2 0 0 1 0 Eqs. (5){(7) can be easily understood from Eq. (4): 3 0 l1 2 0 4 0 l 0 0 2 P1 = c1l1 + c12l2; (5) a i1: Angle between zi1 and zi around xi1; b ai1 : Distance between axes zi1 and zi throughout xi1; P2 = s1l1 + s12l2; (6) c i : Angle between xi1 and xi around zi; d di : Distance between axes xi1 and xi throughout zi. P3 = d3: (7) 2.2.1. Calculation of 1 angle lengths of the other two joints. The length of d3 is Eqs. (5) and (6) are rearranged as follows: calculated considering the height of the gripper. The 2 2 transformation matrices are obtained as in Eq. (2) by (c12l2) = (P1 c1l1) ; (8) the D-H method: 2 2 (s12l2) = (P2 s1l1) : (9) 2 3 2 3 1 0 0 0 c1 s1 0 l1 Eqs. (8) and (9) are summed up together as follows: 6 7 6 7 0 60 1 0 0 7 1 6s1 c1 0 07 1T =4 5 ; 2T =4 5 ; 2 2 2 2 0 0 1 d3 0 0 1 0 l2 = P1 P2 + l1 2l1(P1c1 + P2s1): (10) 0 0 0 1 0 0 0 1 Eq. (11) is obtained when b1 is used instead of (P1c1 + 2 3 P2s1): c2 s2 0 l2 6s c 0 07 2 2 2 2 2T = 6 2 2 7 : (2) l2 = P1 P2 + l1 2l1b1: (11) 3 4 0 0 1 05 0 0 0 1 Figure 2 shows the 1 derivation illustration. Due to the existence of b1, v1 also can be derived by analytical The abbreviations c and s represent the terms \cosine" methods as in Eq. (13). The variables in Figure 2 are and \sine". The DH parameters are given in Table 1. calculated as follows: b = (P c + P s ); (12) The forward kinematic matrix is obtained through 1 1 1 2 1 Eq. (3) by the product of the transformation matrices. v1 = (P1s1 + P2c1); (13) 2 3 2 2 2 c12 s12 0 c1l1 + c12l2 r = v1 + b1; (14) 6 7 0 6s12 c12 0 s1l1 + s12l27 3T = 4 5 : (3) 2 2 2 0 0 1 d3 r = P1 + P2 ; (15) 0 0 0 1 q v = P 2 + P 2 b2; (16) 2.2.