Handling Four DOF Robot to Move Objects Based on Color and Weight using Fuzzy Logic Control

Emmanuel Agung Nugroho, Joga Dharma Setiawan, M. Munadi

Abstract


Manipulators are increasingly used in industry to improve efficiency in jobs that require precision, long duration, and repetitive work. This research was conducted on a laboratory scale to control manipulators on a pick-and-place system in the product storage and packing area. The object of this research is a four-degree-of-freedom (4-DOF) manipulator controlled using a fuzzy logic system. The hardware used is a conveyor machine to model the product delivery process, Dobot Magician as a 4-DOF manipulator, HX711 load cell serves as a weight sensor, TCS-3200 serves as a color sensor, and Arduino Mega 2560 as a controller. The software used is Dobot Studio as the main program to control the movement of the robot and Matlab to develop the Fuzzy Logic Control (FLC) function, which is embedded in the Arduino. Fuzzy logic control processes weight variables and color variables read by sensors as information data to control the movement of the manipulator. The results showed that the manipulator was able to pick up and place objects according to the path-planning coordinates. The testing data states that the precision and accuracy of the average coordinates of product pick and place against the path planning has an error deviation of 1.8%.

Keywords


Manipulator 4 Degree of Freedom; Fuzzy Logic Control; Path Planning; Arduino Mega 2560; Loadcell HX711; Color Sensor TCS3200.

Full Text:

PDF

References


N. Simaan, R. M. Yasin, and L. Wang, “Medical technologies and challenges of robot-assisted minimally invasive intervention and diagnostics,” Annu. Rev. Control. Robot. Auton. Syst., vol. 1, pp. 465–490, 2018.

E. Tosello, N. Castaman, and E. Menegatti, “Using robotics to train students for industry 4.0,” Ifac-Papersonline, vol. 52, no. 9, pp. 177–183, 2019.

X. Jin et al., “Visual-based data exchange system for internal and external networks in physical isolation,” Cogn. Robot., vol. 1, pp. 134–144, 2021.

M. R. Islam, M. A. Rahaman, M. A. U. Zaman, and M. Habibur, "Cartesian trajectory based control of dobot robot," in Proc. Int. Conf. Ind. Eng. Operations Manage, pp. 1507-1517, 2019.

M. A. Abo-Sinna, Y. Y. Abo-Elnaga, and A. A. Mousa, “An interactive dynamic approach based on hybrid swarm optimization for solving multiobjective programming problem with fuzzy parameters,” Appl. Math. Model., vol. 38, no. 7–8, pp. 2000–2014, 2014, doi: 10.1016/J.Apm.2013.10.013.

A.-V. Duka, “Neural network based inverse kinematics solution for trajectory tracking of a robotic arm,” Procedia Technol., vol. 12, pp. 20–27, 2014, doi: 10.1016/J.Protcy.2013.12.451.

M. Alebooyeh and R. J. Urbanic, “Neural network model for identifying workspace, forward and inverse kinematics of the 7-dof yumi 14000 abb collaborative robot,” Ifac-Papersonline, vol. 52, no. 10, pp. 176–181, 2019, doi: 10.1016/J.Ifacol.2019.10.019.

M. Soori, B. Arezoo, and R. Dastres, “Artificial intelligence, machine learning and deep learning in advanced robotics, a review,” Cogn. Robot., vol. 3, pp. 54–70, 2023, doi: 10.1016/J.Cogr.2023.04.001.

S. A. Kouritem, M. I. Abouheaf, N. Nahas, and M. Hassan, "A multi-objective optimization design of industrial robot arms," Alexandria Engineering Journal, vol. 61, no. 12, pp. 12847-12867, 2022.

R. Holubek, M. Janícek, and G. O. Tirian, “Verification of the voice control modification of robot-DOBOT Magician depending to change voice frequency,” J. Phys. Conf. Ser., vol. 2212, no. 1, 2022, doi: 10.1088/1742-6596/2212/1/012016.

S. Chakraborty and P. S. Aithal, “Open Loop Automated Baby Cradle Using Dobot Magician and C#,” Int. J. Appl. Eng. Manag. Lett., vol. 6, no. 1, pp. 344–349, 2022, doi: 10.47992/Ijaeml.2581.7000.0141.

P. S. Tsai, T. F. Wu, J. Y. Chen, And F. H. Lee, “Drawing System With Dobot Magician Manipulator Based On Image Processing,” Machines, vol. 9, no. 12, 2021, doi: 10.3390/Machines9120302.

N. O. M. Chilo, L. F. C. Ccari, E. Supo, E. S. Espinoza, Y. S. Vidal, and L. Pari, "Optimal Signal Processing for Steady Control of a Robotic Arm Suppressing Hand Tremors for EOD Applications," IEEE Access, vol. 11, pp. 13163-13178, 2023.

M. Slim, N. Rokbani, B. Neji, M. A. Terres, and T. Beyrouthy, "Inverse Kinematic Solver Based on Bat Algorithm for Robotic Arm Path Planning," Robotics, vol. 12, no. 2, p. 38, 2023.

P. P. Reboucas Filho, S. P. P. da Silva, V. N. Praxedes, J. Hemanth, and V. H. C. de Albuquerque, "Control of singularity trajectory tracking for robotic manipulator by genetic algorithms," Journal of computational science, vol. 30, pp. 55-64, 2019.

D. Osiński and D. Jasińska-Choromańska, “Kinematic structure of turning modules in orthotic robots,” Procedia Eng., vol. 177, pp. 450–454, 2017, doi: 10.1016/J.Proeng.2017.02.244.

Z. Yang, X. Pan, Y. Wang, and W. Tang, “Kinematics and dynamics analysis of the main motion system of reciprocating machine tools,” Iop Conf. Ser. Mater. Sci. Eng., vol. 394, no. 3, 2018, doi: 10.1088/1757-899x/394/3/032067.

C. A. My and V. M. Hoan, “Kinematic and dynamic analysis of a serial manipulator with local closed loop mechanisms,” Vietnam J. Mech., vol. 41, no. 2, pp. 141–155, 2019, doi: 10.15625/0866-7136/13073.

J. Vavro, J. Vevro, P. Kováčiková, and R. Bezdedová, “Kinematic and dynamic analysis of planar mechanisms by means of the solid works software,” Procedia Eng., vol. 177, pp. 476–481, 2017, doi: 10.1016/J.Proeng.2017.02.248.

T. O. Terefe, H. G. Lemu, and T. B. Tuli, “Kinematic modeling and analysis of a walking machine (robot) leg mechanism on a rough terrain,” Adv. Sci. Technol. Res. J., vol. 13, no. 3, p. 43–53, 2019, doi: 10.12913/22998624/109792.

O. Hock and J. Šedo, “Forward and inverse kinematics using pseudoinverse and transposition method for robotic arm dobot,” In Kinematics, Intech, 2017.

S. Kucuk and Z. Bingul. Robot kinematics: Forward and inverse kinematics (pp. 117-148). London, UK: INTECH Open Access Publisher, 2006.

N. Wagaa, H. Kallel, and N. Mellouli, "Analytical and deep learning approaches for solving the inverse kinematic problem of a high degrees of freedom robotic arm," Engineering Applications of Artificial Intelligence, vol. 123, p. 106301, 2023.

S. Dikmenli, “Forward & inverse kinematics solution of 6-dof robots those have offset & spherical wrists,” Eurasian J. Sci. Eng. Technol., vol. 3, no. 1, pp. 14–28, 2022, doi: 10.55696/Ejset.1082648.

D. R. Parhi, B. B. V. L. Deepak, D. Nayak, and A. Amrit, "Forward and inverse kinematic models for an articulated robotic manipulator," International Journal of Artificial Intelligence and Computational Research, vol. 4, no. 2, pp. 103-109, 2012.

M. Almaged, “Forward and inverse kinematic analysis and validation of the abb irb 140 industrial robot,” Int. J. Electron. Mech. Mechatronics Eng., vol. 7, no. 2, pp. 1383–1401, 2017.

M. Ben-Ari and F. Mondada. Elements of robotics. Springer Nature, 2017.

J. Zhu and F. Tian, “Kinematics analysis and workspace calculation of a 3-dof manipulator,” Iop Conf. Ser. Earth Environ. Sci., vol. 170, no. 4, 2018, doi: 10.1088/1755-1315/170/4/042166.

F. Gonçalves, T. Ribeiro, A. F. Ribeiro, G. Lopes, and P. Flores, “A recursive algorithm for the forward kinematic analysis of robotic systems using euler angles,” Robotics, vol. 11, no. 1, pp. 1–20, 2022, doi: 10.3390/Robotics11010015.

H. Z. Ting, M. Hairi, M. Zaman, M. Ibrahim, and A. Moubark, "Kinematic analysis for trajectory planning of open-source 4-DoF robot arm," International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, pp. 769-777, 2021.

M. Anschober, R. Edlinger, R. Froschauer, and A. Nüchter, “Inverse kinematics of an anthropomorphic 6r robot manipulator based on a simple geometric approach for embedded systems,” Robotics, vol. 12, no. 4, 2023, doi: 10.3390/Robotics12040101.

A. Fomin, A. Antonov, V. Glazunov, and Y. Rodionov, "Inverse and forward kinematic analysis of a 6-DOF parallel manipulator utilizing a circular guide," Robotics, vol. 10, no. 1, p. 31, 2021.

B. Tam, T. A. O. Linh, T. Nguyen, T. Nguyen, H. Hasegawa, and D. Watanabe, “DE-based algorithm for solving the inverse kinematics on a robotic arm manipulators,” J. Phys. Conf. Ser., vol. 1922, no. 1, 2021, doi: 10.1088/1742-6596/1922/1/012008.

S. Kucuk and Z. Bingul, “Inverse kinematics solutions for industrial robot manipulators with offset wrists,” Appl. Math. Model., vol. 38, no. 7–8, pp. 1983–1999, 2014, doi: 10.1016/J.Apm.2013.10.014.

D. Rodríguez-Guerra, G. Sorrosal, I. Cabanes, and C. Calleja, "Human-Robot Interaction Review: Challenges and Solutions for Modern Industrial Environments," in IEEE Access, vol. 9, pp. 108557-108578, 2021, doi: 10.1109/ACCESS.2021.3099287..

H. P. Nurba, D. Hadian, N. Lestari, K. A. Munastha, H. Mistialustina, and E. Rachmawati, "Performance Evaluation of 3 DOF Arm Robot With Forward Kinematics Denavit-Hartenberg Method For Coffee Maker Machine," 2022 16th International Conference on Telecommunication Systems, Services, and Applications (TSSA), pp. 1-6, 2022, doi: 10.1109/TSSA56819.2022.10063918..

C. Faria, J. L. Vilaça, S. Monteiro, W. Erlhagen, and E. Bicho, "Automatic Denavit-Hartenberg Parameter Identification for Serial Manipulators," IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society, pp. 610-617, 2019, doi: 10.1109/IECON.2019.8927455.

C. Corina, E. Pop, and M. Leba, "Modeling and Simulation for a 3 D Robot Controlled by a Pick and Place Application," in WSEAS International Conference. Proceedings. Mathematics and Computers in Science and Engineering (No. 10). World Scientific and Engineering Academy and Society, 2009.

A. A. Hayat, R. G. Chittawadigi, A. D. Udai, and S. K. Saha, “Identification of denavit-hartenberg parameters of an industrial robot,” Acm Int. Conf. Proceeding Ser., pp. 4–9, 2013, doi: 10.1145/2506095.2506121.

N. Correll, “Introduction To Autonomous Robots,” J. Chem. Inf. Model., vol. 53, no. 9, pp. 1689–1699, 2016.

J. A. Soares, “Urban sociology and research methods on neighborhoods and health,” Handb. Urban Heal., pp. 361–378, 2006, doi: 10.1007/0-387-25822-1_18.

L. Qingsheng and J. Andika, “Analysis of kinematic for legs of a hexapod using denavit-hartenberg convention,” Sinergi, vol. 22, no. 2, p. 69, 2018, doi: 10.22441/Sinergi.2018.2.001.

E. Akindele Ayoola, I. Awodeyi Afolabi, O. Matthews Victor, A. Alashiri Olaitan, K. Idowu Oriyomi, and J. Olaloye Folarin, "Development of an Electronic Weighing Indicator for Digital Measurement," International Research Journal of Engineering and Technology, vol. 5, no. 9, pp. 19-25, 2018.

A. Renfrew, “Book review: introduction to robotics: mechanics and control,” Int. J. Electr. Eng. Educ., vol. 41, no. 4, pp. 388–388, 2004, doi: 10.7227/Ijeee.41.4.11.

I. Agustian, N. Daratha, R. Faurina, A. Suandi, and S. Sulistyaningsih, “Robot Manipulator Control with Inverse Kinematics PD-Pseudoinverse Jacobian and Forward Kinematics Denavit Hartenberg,” J. Elektron. Dan Telekomun., vol. 21, no. 1, p. 8, 2021, doi: 10.14203/Jet.V21.8-18.

D. K. Jain, S. Neelakandan, T. Veeramani, S. Bhatia, and F. H. Memon, "Design of fuzzy logic based energy management and traffic predictive model for cyber physical systems," Computers and Electrical Engineering, vol. 102, p. 108135, 2022.

C. Mavroidis, E. Lee, and M. Alam, "A new polynomial solution to the geometric design problem of spatial RR robot manipulators using the denavit and Hartenberg parameters," J. Mech. Des., vol. 123, no. 1, pp. 58-67, 2001.

A. K. Kovalchuk and F. K. Akhmetova, “Denavit-Hartenberg Coordinate System for Robots with Tree-Like Kinematic Structure,” vol. 5, no. 4, pp. 244–254, 2016.

L. Radavelli, R. Simoni, E. De Pieri, and D. Martins, "A comparative study of the kinematics of robots manipulators by Denavit-Hartenberg and dual quaternion," Mecánica Computacional, vol. 31, no. 15, pp. 2833-2848, 2012.

H. J. Chung et al. A robust formulation for prediction of human running. SAE Technical Paper, 2007.

H. Afrisal, A. D. Setiyadi, M. A. Riyadi, R. Ismail, O. Toirov, and I. Setiawan, "Performance Analysis of 4-DOF RPRR Robot Manipulator Actuation Strategy for Pick and Place Application in Healthcare Environment," International Journal on Advanced Science, Engineering and Information Technology, vol. 12, no. 6, pp. 2258-2265, 2022.

C. Klug, D. Schmalstieg, T. Gloor, and C. Arth, “A Complete Workflow for Automatic Forward Kinematics Model Extraction of Robotic Total Stations using the Denavit-Hartenberg Convention,” J. Intell. Robot. Syst. Theory Appl., vol. 95, no. 2, pp. 311–329, 2019, doi: 10.1007/S10846-018-0931-4.

E. A. Nugroho, N. R. Wibowo, R. Rizalludin, and M. Ruswanda, "Fuzzy system as four-joint robot movement control for moving goods based on time and object color," Jurnal Ramatekno, vol. 2, no. 2, pp. 7-15, 2022.

S. N. Sivanandam, S. Sumathi, and S. N. Deepa. Introduction to Fuzzy Logic using MATLAB. Springer Science & Business Media, 2006.

C. Y. Chen, M. G. Her, Y. C. Hung, and M. Karkoub, “Approximating a Robot Inverse Kinematics Solution using Fuzzy Logic Tuned by Genetic Algorithms,” Int. J. Adv. Manuf. Technol., vol. 20, no. 5, pp. 375–380, 2002, doi: 10.1007/S001700200166.

M. Crenganiș, M. Tera, C.Biriș, and C. Gîrjob, "Dynamic analysis of a 7 DOF robot using fuzzy logic for inverse kinematics problem," Procedia computer science, vol. 162, pp. 298-306, 2019.

A. K. Varshney and V. Torra, “Literature Review of the Recent Trends and Applications in Various Fuzzy Rule-Based Systems,” Int. J. Fuzzy Syst., vol. 25, no. 6, pp. 2163–2186, 2023, doi: 10.1007/S40815-023-01534-W.

M. R. Mufid, N. R. Kusuma Saginta Putri, A. Fariza, and Mu'arifin, "Fuzzy Logic and Exponential Smoothing for Mapping Implementation of Dengue Haemorrhagic Fever in Surabaya," 2018 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC), pp. 372-377, 2018, doi: 10.1109/KCIC.2018.8628533..

S. Maheswari, M. Shalini, and T. L. Yookesh, “Defuzzification Formula for Modelling and Scheduling a Furniture Fuzzy Project Network,” Int. J. Eng. Adv. Technol., vol. 9, no. 5, pp. 279–283, 2019, doi: 10.35940/Ijeat.A1048.1291s519.

N. Sabounchi, K. Triantis, S. Sarangi, and S. Liu, “Fuzzy Modeling of Linguistic Variables in a System Dynamics Context,” Proc. 29th Int. Conf. Syst. Dyn. Soc., pp. 1–30, 2011.

P. Hofmann, "Defuzzification strategies for fuzzy classifications of remote sensing data," Remote Sensing, vol. 8, no. 6, p. 467, 2016.

K. S. Gilda and S. L. Satarkar, "Analytical overview of defuzzification methods," International Journal of Advance Research, Ideas and Innovations in Technology, vol. 6, no. 2, pp. 359-365, 2020.

S. Razvarz and M. Tahmasbi, “Fuzzy Equations and Z-Numbers for Nonlinear Systems Control,” Procedia Comput. Sci., vol. 120, pp. 923–930, 2017, doi: 10.1016/J.Procs.2017.11.327.

D. Behera and S. Chakraverty, “Solution to Fuzzy System of Linear Equations with Crisp Coefficients,” Fuzzy Inf. Eng., vol. 5, no. 2, pp. 205–219, 2013, doi: 10.1007/S12543-013-0138-0.

V. B. Tarassov, “Development of Fuzzy Logics: from Universal Logic Tools to Natural Pragmatics and Non-Standard Scales,” Procedia Comput. Sci., vol. 120, no. 2017, pp. 908–915, 2017, doi: 10.1016/J.Procs.2017.11.325.

B. Orazbayev, E. Ospanov, N. Kissikova, N. Mukataev, and K. Orazbayeva, “Decision-Making in the Fuzzy Environment on the Basis of Various Compromise Schemes,” Procedia Comput. Sci., vol. 120, pp. 945–952, 2017, doi: 10.1016/J.Procs.2017.11.330.

J. Gallardo-Alvarado, M. A. Garcia-Murillo, L. A. Alcaraz-Caracheo, F. J. Torres, and X. Y. Sandoval-Castro, "Forward kinematics and singularity analyses of an uncoupled parallel manipulator by algebraic screw theory," IEEE Access, vol. 10, pp. 4513-4522, 2021.

A. N. Sharkawy, "Forward and inverse kinematics solution of a robotic manipulator using a multilayer feedforward neural network," Journal of Mechanical and Energy Engineering, vol. 6, no. 2, 2022.

H. Ren and P. Ben-Tzvi, "Learning inverse kinematics and dynamics of a robotic manipulator using generative adversarial networks," Robotics and Autonomous Systems, vol. 124, p. 103386, 2020.

A. F. Hastawan et al., "Comparison of testing load cell sensor data sampling method based on the variation of time delay," in IOP Conference Series: Earth and Environmental Science, vol. 700, no. 1, p. 012018, 2021.

M. S. Surbakti et al., “Development of Arduino Uno-Based Tcs3200 Color Sensor and its Application on the Determination of Rhodamine B Level in Syrup,” Indones. J. Chem., vol. 22, no. 3, pp. 630–640, 2022, doi: 10.22146/Ijc.69214.

A. Najmurrokhman, K. Kusnandar, F. Maulana, B. Wibowo, and E. Nurlina, "Design of a prototype of manipulator arm for implementing pick-and-place task in industrial robot system using TCS3200 color sensor and ATmega2560 microcontroller," in Journal of Physics: Conference Series, vol. 1375, no. 1, p. 012041, 2019.

R. Das, “Automation of Tank Level using PLC and Establishment of HMI by Scada,” Iosr J. Electr. Electron. Eng., vol. 7, no. 2, pp. 61–67, 2013, doi: 10.9790/1676-0726167.

B. M. Yilmaz, E. Tatlicioglu, A. Savran, and M. Alci, "Adaptive fuzzy logic with self-tuned membership functions based repetitive learning control of robotic manipulators," Applied Soft Computing, vol. 104, p. 107183, 2021.

F. Wildani, R. Mardiati, E. Mulyana, A. E. Setiawan, R. R. Nurmalasari, and N. Sartika, "Fuzzy Logic Control for Semi-Autonomous Navigation Robot Using Integrated Remote Control," 2022 8th International Conference on Wireless and Telematics (ICWT), pp. 1-5, 2022, doi: 10.1109/ICWT55831.2022.9935458.

Arduino. Arduino Mega 2560 Datasheet. Power, p. 3, 2015.

M. Janíček, R. Ružarovský, K. Velíšek, and R. Holubek, “Analysis of Voice Control of a Collaborative Robot,” J. Phys. Conf. Ser., vol. 1781, no. 1, 2021, doi: 10.1088/1742-6596/1781/1/012025.

M. Marsono, Y. Yoto, A. Suyetno, and R. Nurmalasari, "Design and programming of 5 axis manipulator robot with grblgru open source software on preparing vocational students’ robotic skills," Journal of Robotics and Control (JRC), vol. 2, no. 6, pp. 539-545, 2021.

F. C. Can, “Arduino Based Planar Two DoF Robot Manipulator,” J. Mech. Eng. Autom., vol. 8, no. 3, 2018, doi: 10.17265/2159-5275/2018.03.002.

L. Stěpničkova, M. Stěpnička, and D. Sikora, “Fuzzy Rule-Based Ensemble with use of Linguistic Associations Mining for Time Series Prediction,” 8th Conf. Eur. Soc. Fuzzy Log. Technol. Eusflat 2013 - Adv. Intell. Syst. Res., vol. 32, pp. 408–415, 2013, doi: 10.2991/Eusflat.2013.63.

V. Afrian and S. Riyadi, “Comparison Of Different Rule Base Matrix In Fuzzy Logic Controller,” J. Phys. Conf. Ser., vol. 1444, no. 1, 2020, doi: 10.1088/1742-6596/1444/1/012018.




DOI: https://doi.org/10.18196/jrc.v4i6.20087

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Emmanuel Agung Nugroho, Joga Dharma Setiawan, M. Munadi

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 


Journal of Robotics and Control (JRC)

P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Peneliti Teknologi Teknik Indonesia
Published by Universitas Muhammadiyah Yogyakarta in collaboration with Peneliti Teknologi Teknik Indonesia, Indonesia and the Department of Electrical Engineering
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrcofumy@gmail.com


Kuliah Teknik Elektro Terbaik