Pattern recognition based movement control and gripping forces control system on arm robot model using LabVIEW
Most arm robot has an inefficient operating time because it requires operator to input destination coordinates. Besides, main problem of arm robot is object’s vulnerability when it is manipulated by the robot. This research goals is to develop an arm robot control system which has ability to automatically detect object using image processing in order to reduce operating time. It is also able to control gripping force for eliminating damage to objects caused by robot gripper. This research is implemented in LabVIEW 2011 software to control arm robot model which can represent industrial scale robot. The software is designed with informative visualization to help user learn and understand robotic control concept deeply. The system can automatically detect object position based on pattern recognition method which has four steps: pre-processing process to initialize picture taken by camera, segmentation process for separating object from the background, classification process to determine characteristics of object, and position estimation process to estimate object position in the picture. The object’s position data are then calculated by using kinematic equation to control the robot’s motion. The results show that the system is able to detect object and move the robot automatically with accuracy rate in x-axis is 95.578 % and in y-axis is 92.878 %. The system also implements modified PI control method with FSR as input to control gripping force with maximum overshoot value <10 %. Arm robot model control system developed is successfully meet the expectation. The system control can be implemented to industrial scale arm robot with several modification because of kinematic similarity between model and industrial scale robot.
A. O. Oke, A. Afolabi, “Development of a robotic arm for dangerous object disposal,” in Proc. 2014 6th International Conference on computer Science and Information Technology (CSIT), pp. 153-160, March, 2014.
S. O. Adebola, O. A. Odejobi, O. A. Koya, “Design and implementation of a locally-sourced robotic arm,” Proc. AFRICON, pp. 1-4, Sep. 2013.
T. Yoshimi, N. Iwata, M. Mizukawa, Y. Ando, “Picking up operation of thin objects by robot ARM with two-fingered parallel soft gripper,” Proc. Advanced Robotics and its Social Impacts (ARSO), pp. 7-12, May, 2012.
M. Atas, Y. Dogan, S. Atas, “Chess playing robotic arm,” Proc. Processing and Communications Applications Conference (SIU), pp. 1171-1171, April, 2014.
M. W. Spong, S. Hutchinson, and M. Vidyasagar, Robot modeling and control. 2nd ed., Newyork: John Wiley & Sons, inc., pp. 5-12, 2012.
A. R. Al-Tahtawi, M. Agni, T. D. Hendrawati, “Small-scale robot arm design with pick and place mission based on inverse kinematics”, Journal of Robotics and Control, vol. 2, pp. 469-475, Nov., 2021.
M. Dechrit, “PC-based 5DOF industrial robotic arm with object color sorting by image processing,” Journal of Sci. Tech. SNRU, vol. 10, no. 3 pp. 148-155, Aug. 2018.
M. J. Ansari, A. Amir, M. A. Hoque, “Microcontroller based robotic arm: operational to gesture and automated mode,” in Proc. ICEEICT, Apr., 2014.
R. S. Pol, S. Giri, A. Ravishankar, and V. Ghode, "LabVIEW based four DoF robotic arm," 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1791-1798, Sep., 2016.
P. Andhare and S. Rawat, “Pick and place industrial robot controller with computer vision,” Proc. - 2nd Int. Conf. Comput. Commun. Control Autom. (ICCUBEA), Aug., 2016.
Hu. Huosheng, G Palmieri, M. Palpacelli, M. Battistelli, M.Callegari, “A comparison between position-based and imagebased dynamic visual servoings in the control of a translating parallel manipulator,” Journal of Robotics, pp. 1-11, May, 2012.
D. Xu, “A tutorial for monocular visual servoing,” in Acta Automation Sinica, vol. 44, no. 10, pp. 1729-1746, 2018.
J. T. Feddema, C. S. George Lee, and O. R. Mitchell, “Weighted selection of image features for resolved rate visual feedback control,” IEEE Transactions on Robotics and Automation, vol. 7, pp. 31–47, 1991.
J. Oh, H. Bae, J. H. Oh, “Analytic inverse kinematics considering the joint constraints and self-collision for redundant 7DOF manipulator,” in Proc. IRC, pp. 123-128, Apr., 2017.
W. Xu, Z. Mu, T. Liu, B. Liang, “A modified modal method for solving the mission-oriented inverse kinematics of hyperredundant space manipulators for on-orbit servicing,” Acta Astronautica, vol. 139, pp. 54-66, Oct., 2017.
M. R. Elhami and I. Dashti, “A new approach to the solution of robot kinematics based on relative transformation matrices,” in Journal IJRA, vol. 5, no. 3, pp. 213-222, Sep., 2016.
Z. Amin and H. Ahmadi, “Inverse kinematic of european robotic arm based on a new geometrical approach,” in Journal AJME, vol. 5, no. 1, pp. 13-48, March, 2020.
M. Amin and S. Mehmet, “Kinematics modeling of a 4-DOF robotic arm," in Proc. ICCAR, pp. 87-91, May, 2015.
Metrics powered by PLOS ALM
Copyright (c) 2022 Journal of Mechatronics, Electrical Power, and Vehicular Technology
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.