Top > JACIII > Simulated vs Actual Application of Symbiotic Model on Six Whee ...

single-jc.php

JACIII Vol.28 No.1 pp. 12-20
doi: 10.20965/jaciii.2024.p0012
(2024)

Research Paper:

Views over last 60 days: 121

Simulated vs Actual Application of Symbiotic Model on Six Wheel Modular Multi-Agent System for Linear Traversal Mission

Arvin H. Fernando*1,† ORCID Icon, Laurence A. Gan Lim*1 ORCID Icon, Argel A. Bandala*2 ORCID Icon, Ryan Rhay P. Vicerra*3 ORCID Icon, Elmer P. Dadios*3 ORCID Icon, Marielet A. Guillermo*3 ORCID Icon, and Raouf N. G. Naguib*4 ORCID Icon

*1Department of Mechanical Engineering, De La Salle University
2401 Taft Avenue, Malate, Manila 1004, Philippines

†Corresponding author

*2Department of Electronics and Computer Engineering, De La Salle University
2401 Taft Avenue, Malate, Manila 1004, Philippines

*3Department of Manufacturing Engineering and Management, De La Salle University
2401 Taft Avenue, Malate, Manila 1004, Philippines

*4Liverpool Hope University
Hope Park, Taggart Avenue, Liverpool L 9, United Kingdom

Received:
March 3, 2023
Accepted:
July 13, 2023
Published:
January 20, 2024
Creative Commons License
Keywords:
differential drive kinematics, modular reconfigurable robot, multi-agent system, odometry, symbiosis
Abstract

Constant demand for sustainable mechanisms to perform heavy and risky tasks has driven more robotics innovations to arise. Modular reconfigurable robotics system is one of these promising technologies that are continuously explored. Homogeneous types, to be specific, can accomplish similar missions at the same time as individual and heavier missions as an integrated system. This paper presents an analysis of the carrying capacity of a six-wheeled modular multi-agent system using the symbiotic model. The objective is to determine the resulting symbiotic relationship of a given configuration and module state combinations. The results show that the dominant relationship among the trials for linear traversal mission is commensalism. That means, the system neither benefits nor gets harmed from the symbiosis formed. This is true both in simulated and actual test environments although the percentage difference is about 12%. MATLAB Simulink was used for simulation while Maqueen robot in a 3D-printed chassis was used for actual testing. With this study, future configurations for several other missions such as object tracking and ramp climbing can be assessed using the same approach so that possible fault occurrence during operations can be prevented since the developed analysis method is performed prior to the deployment of the system.

Cite this article as:
A. Fernando, L. Lim, A. Bandala, R. Vicerra, E. Dadios, M. Guillermo, and R. Naguib, “Simulated vs Actual Application of Symbiotic Model on Six Wheel Modular Multi-Agent System for Linear Traversal Mission,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.1, pp. 12-20, 2024.
Data files:
References
  1. [1] A. M. Romanov, V. D. Yashunskiy, and W.-Y. Chiu, “A Modular Reconfigurable Robot for Future Autonomous Extraterrestrial Missions,” IEEE Access, Vol.9, pp. 147809-147827, 2021. https://doi.org/10.1109/ACCESS.2021.3124951
  2. [2] M. Haire, X. Xu, L. Alboul, J. Penders, and H. Zhang, “Ship Hull Repair Using a Swarm of Autonomous Underwater Robots: A Self-Assembly Algorithm,” 2019 European Conf. on Mobile Robots (ECMR), Prague, Czech Republic, 2019. https://doi.org/10.1109/ECMR.2019.8870910
  3. [3] H. Kawano, “Linear Heterogeneous Reconfiguration of Cubic Modular Robots via Simultaneous Tunneling and Permutation,” 2019 Int. Conf. on Robotics and Automation (ICRA), Montreal, QC, Canada, pp. 332-338, 2019. https://doi.org/10.1109/ICRA.2019.8793594
  4. [4] S. H. Turlapati, A. Srivastava, K. M. Krishna, and S. V. Shah, “Detachable modular robot capable of cooperative climbing and multi agent exploration,” 2017 IEEE Int. Conf. on Robotics and Automation (ICRA), Singapore, pp. 255-260, 2017. https://doi.org/10.1109/ICRA.2017.7989032
  5. [5] S. Lim, S. Wang, B. Lennox, and F. Arvin, “BeeGround – An Open-Source Simulation Platform for Large-Scale Swarm Robotics Applications,” 2021 7th Int. Conf. on Automation, Robotics and Applications (ICARA), Prague, Czech Republic, pp. 75-79, 2021. https://doi.org/10.1109/ICARA51699.2021.9376494
  6. [6] T. Mina, S. S. Kannan, W. Jo, and B.-C. Min, “Adaptive Workload Allocation for Multi-Human Multi-Robot Teams for Independent and Homogeneous Tasks,” IEEE Access, Vol.8, pp. 152697-152712, 2020. https://doi.org/10.1109/ACCESS.2020.3017659
  7. [7] T. Zhu, G. I. Fernandez, C. Togashi, Y. Liu, and D. Hong, “Feasibility Study of LIMMS, A Multi-Agent Modular Robotic Delivery System with Various Locomotion and Manipulation Modes,” 2022 19th Int. Conf. on Ubiquitous Robots (UR), Jeju, Korea, pp. 30-37, 2022. https://doi.org/10.1109/UR55393.2022.9826272
  8. [8] E. Hourany, C. Stephan, A. Makhoul, B. Piranda, B. Habib, and J. Bourgeois, “Self-Reconfiguration of Modular Robots Using Virtual Forces,” 2021 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Prague, Czech Republic, pp. 6948-6953, 2021. https://doi.org/10.1109/IROS51168.2021.9635889
  9. [9] Y. Li, H. Fang, J. Chen, and C. Yu, “Distributed Cooperative Fault Detection for Multiagent Systems: A Mixed H∞/H2 Optimization Approach,” IEEE Trans. on Industrial Electronics, Vol.65, No.8, pp. 6468-6477, 2018. https://doi.org/10.1109/TIE.2017.2786235
  10. [10] V. I. Yukalov, E. P. Yukalova, and D. Sornette, “Modeling symbiosis by interactions through species carrying capacities,” Physica D: Nonlinear Phenomena, Vol.241, Issue 15, pp. 1270-1289, 2012. https://doi.org/10.1016/j.physd.2012.04.005
  11. [11] S. Mabu, M. Obayashi, and T. Kuremoto, “Reinforcement Learning with Symbiotic Relationships for Multiagent Environments,” J. of Robotics, Networking and Artificial Life, Vol.2, Issue 1, pp. 40-45, 2015. https://doi.org/10.2991/jrnal.2015.2.1.10
  12. [12] P. Tokekar, J. V. Hook, D. Mulla, and V. Isler, “Sensor Planning for a Symbiotic UAV and UGV System for Precision Agriculture,” IEEE Trans. on Robotics, Vol.32, No.6, pp. 1498-1511, 2016. https://doi.org/10.1109/TRO.2016.2603528
  13. [13] A. H. Fernando and L. A. Gan Lim, “Model-Based Simulation of a Mini Differential Drive Robot,” 2021 IEEE 13th Int. Conf. on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), Manila, Philippines, 2021. https://doi.org/10.1109/HNICEM54116.2021.9731981
  14. [14] R. Singh, G. Singh, and V. Kumar, “Control of closed-loop differential drive mobile robot using forward and reverse kinematics,” 2020 3rd Int. Conf. on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli, India, pp. 430-433, 2020. https://doi.org/10.1109/ICSSIT48917.2020.9214176
  15. [15] A. Stefek, T. V. Pham, V. Krivanek, and K. L. Pham, “Energy Comparison of Controllers Used for a Differential Drive Wheeled Mobile Robot,” IEEE Access, Vol.8, pp. 170915-170927, 2020. https://doi.org/10.1109/ACCESS.2020.3023345
  16. [16] A. H. Fernando and L. A. Gan Lim, “Evaluation of Carrying Capacity for a Modular Mobile Robot in a Linear Configuration,” 2021 Int. Symp. on Electronics and Smart Devices (ISESD), 2021.
  17. [17] A. H. Fernando and L. A. Gan Lim, “Velocity analysis of a six-wheel modular mobile robot using MATLAB-Simulink,” 11th AUN/SEED-Net Regional Conf. on Mechanical and Manufacturing Engineering (RCMEManuE 2020), January 14-15, 2021, 2021.
  18. [18] A. H. Fernando and L. A. Gan Lim, “Symbiotic Approach in a Modular Mobile Robot,” Int. J. of Emerging Trends in Engineering Research, Vol.9, No.5, Article No.602, 2021. https://doi.org/10.30534/ijeter/2021/12952021
  19. [19] M. Steve, “Simscape Multibody Contact Forces Library,” MATLAB Central File Exchange 2020. https://www.mathworks.com/matlabcentral/fileexchange/47417-simscape-multibody-contact-forces-library [Accessed December 13, 2019]
  20. [20] N. Gavin, “MicroMouse Modelling,” Simscape MultiBody, 2017.
  21. [21] R. R. P. Vicerra, E. P. Dadios, A. A. Bandala, and L. A. Gan Lim, “Swarm Robot System for Underwater Communication Network,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, No.5, pp. 769-775, 2014. https://doi.org/10.20965/jaciii.2014.p0769
  22. [22] A. A. Bandala, E. P. Dadios, R. R. P. Vicerra, and L. A. Gan Lim, “Swarming Algorithm for Unmanned Aerial Vehicle (UAV) Quadrotors,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, No.5, 2014. https://doi.org/10.20965/jaciii.2014.p0745
  23. [23] H. Aydt, S. J. Turner, W. Cai, and M. Y. H. Low, “Research issues in symbiotic simulation,” Proc. of the 2009 Winter Simulation Conference (WSC), Austin, TX, USA, pp. 1213-1222, 2009. https://doi.org/10.1109/WSC.2009.5429419
  24. [24] J. R. B. Del Rosario, J. G. Sanidad, A. M. Lim, P. S. L. Uy, A. J. C. Bacar, and M. A. D. Cai, “Modelling and characterization of a maze-solving mobile robot using wall follower algorithm,” Applied Mechanics and Materials, Vol.446, pp. 1245-1249, 2014.
  25. [25] R. A. R. Bedruz, J. Martin, Z. Maningo, A. H. Fernando, A. A. Bandala, R. R. P. Vicerra, and E. P. Dadios, “Dynamic Peloton Formation Configuration Algorithm of Swarm Robots for Aerodynamic Effects Optimization,” 2019 7th Int. Conf. on Robot Intelligence Technology and Applications (RiTA), Daejeon, South Korea, pp. 264-267, 2019. https://doi.org/10.1109/RITAPP.2019.8932871
  26. [26] A. H. Fernando, A. B. Maglaya, and A. T. Ubando, “Optimization of an algae ball mill grinder using artificial neural network,” 2016 IEEE Region 10 Conf. (TENCON), Singapore, pp. 3752-3756, 2016. https://doi.org/10.1109/TENCON.2016.7848762
  27. [27] A. H. Fernando, I. A. V. Marfori, and A. B. Maglaya, “A comparative study between artificial neural network and linear regression for optimizing a hinged blade cross axis turbine,” 2015 Int. Conf. on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), Cebu, Philippines, 2015. https://doi.org/10.1109/HNICEM.2015.7393225

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024