IJBTT

Study of Wall Climbing Robot through the Simulation of Multi-Body Dynamics

Study of Wall Climbing Robot through the Simulation of Multi-Body Dynamics
	© 2022 by IJETT Journal
	Volume-70 Issue-11
	Year of Publication : 2022
	Author : Yeon Taek OH
	DOI : 10.14445/22315381/IJETT-V70I11P214

How to Cite?

Yeon Taek OH, "Study of Wall Climbing Robot through the Simulation of Multi-Body Dynamics," International Journal of Engineering Trends and Technology, vol. 70, no. 11, pp. 138-143, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I11P214

Abstract
This paper studied a robot that allows the exploration platform used for ship surfaces and large steel structures to drive on the wall. Regarding the wall-driving robot, this study proposed a stable operating structure even with the rapid change in the slope of the ship's surface. Wheel-based operating methods are challenging to drive flexibly on curved surfaces. Therefore, the robot was designed to have a rotating joint in the center of the driving robot. The arrangement of wheels is an essential aspect of this structure. They must overlap each other so that the robot wheels can intersect when viewed from the side view. The wheel also serves as a tool to attach to the wall with a circular neodymium magnet. The necessary magnetic force was proposed based on the conditions identified through dynamic modeling. Important factors required for magnetic force setting include platform weight, the angle between the ground and slope, and friction coefficient. Based on the analysis results, the platform was not slid and remained attached to the steel sheet.

Keywords
Exploration robot, Magnetic force, Wall-climbing, Mechanism, Maxwell analysis.

Reference
[1] Kwon S. D, Kim S. J, Kim S. Y, and Kim S. H, “Design of Wall-Climbing Mobile Platform by Modeling of Attachable and Traction Force,” in Proceedings of the 2010 Fall Conference of The Korean Association of Immunologists, Korean Society of Precision Engineering, pp. 239-240, 2010.
[2] Choi. H. R. and Lee. J. H., “Development of Wall Climbing Robot,” in Proceedings of the 1999 Spring Conference of The Korean Association of Immunologists, Korean Society of Precision Engineering, pp. 3-9, 1999.
[3] Kim H, Seo K, Kim J and Kim H, “Design of Tracked Wheel Mechanism for Wall Climbing Robot,” in Proceedings of the 2010 Fall Conference of the Korean Association of Immunologists, Korean Society of Precision Engineering, pp. 215-216, 2010.
[4] Park S. H, Seo K. J, Choi J. R, Kwon D. H, Bang J. H and Kim S. G, “Development of the Wall Climbing Robot Using New Mechanism,” in Proceedings of the 2016 Fall Conference of the Korean Association of Immunologists, Korean Society of Precision Engineering, pp. 150-151, 2016.
[5] Yi H, Kim E and Han S, “Guideline for the Design of Wall-Climbing Mobile Robot Using Permanent Magnetic Wheels,” in Proceedings of the 2002 Fall Conference of The Korean Association of Immunologists, Korean Society of Precision Engineering, pp. 548-553, 2002.
[6] Bradley A. M, Feezor M. D, Singh H and Sorrell F. Y, “Power System for Autonomous Underwater Vehicle,” IEEE Journal of Oceanic Engineering, vol. 26, no. 4, pp. 526-538, 2001. Crossref, https://doi.org/10.1109/48.972089
[7] Daijun X, Xueshan G, Xiaobing W, Ningjun F, Kejie L and Koki K, “Suction Ability Analyses of a Novel Wall Climbing Robot,” Proceedings of IEEE International Conference on Robotics and Biomimetics, pp. 1506-1511, 2006. Crossref, https://doi.org/10.1109/ROBIO.2006.340152
[8] Roan Van Hoa, Nguyen Duc Dien and Lai Khac Lai, "Research and Apply Deep Reinforcement Learning Technology to Control Mobile Robot," SSRG International Journal of Electrical and Electronics Engineering, vol. 8, no. 4, pp. 30-35, 2021. Crossref, https://doi.org/10.14445/23488379/IJEEE-V8I4P106
[9] Han S. C, Lee J. Y and Kim J. H, “Design of Hybrid Magnet Wheels Using 3d Finite Element Analysis for Wall-Climbing Robot,” Journal of the Society of Naval Architects of Korea, vol. 47, no. 1, pp. 88-89, 2010. Crossref, http://dx.doi.org/10.3744/SNAK.2010.47.1.088
[10] Roan Van Hoa, L. K. Lai and Le Thi Hoan, "Mobile Robot Navigation Using Deep Reinforcement Learning in Unknown Environments," SSRG International Journal of Electrical and Electronics Engineering, vol. 7, no. 8, pp. 15-20, 2020. Crossref, https://doi.org/10.14445/23488379/IJEEE-V7I8P104
[11] McEwen R. H, Thomas D, Weber D and Psota F, “Performance of an AUV Navigation System at Arctic Latitudes,” IEEE Journal of Oceanic Engineering, vol. 30, no. 2, pp. 443-454, 2005. Crossref, https://doi.org/10.1109/OCEANS.2003.178387
[12] Nicholson J. W and Healey A. J, “The Present State of Autonomous Underwater Vehicle (AUV) Application and Technologies,” Marine Technology Society Journal, vol. 42, no. 1, pp. 44-52, 2008. Crossref, https://doi.org/10.4031/002533208786861272
[13] Nguyen Duc Dien, Nguyen Duc Duong, Vu Anh Nam and Tran Thi Huong, "Building Environmental Awareness System for Mobile Robot Operating in Indoor Environment on ROS Platform," SSRG International Journal of Electrical and Electronics Engineering, vol. 8, no. 1, pp. 32-36, 2021. Crossref, https://doi.org/10.14445/23488379/IJEEE-V8I1P106
[14] OH Y. T., “Evaluation of Joint Driving Torque and Finite Element Analysis in Articulate Robot Through the Simulation of Multi-Body Dynamics,” International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 11, pp. 682-686, 2019. Crossref, http://doi.org/10.35940/ijitee.K1725.0981119
[15] OH, Yeon Taek, “Study of Wall Climbing Robot Having Magnetic Force,” Journal of the Korean Society of Mechanical Technology, vol. 22, no. 6, pp. 1001-1005, 2022.
[16] Sibenac M, Podder T, Kirkwood W and Thomas H, “Autonomous Underwater Vehicles for Ocean Research: Current Needs and State of the Art Technologies,” Marine Technology Society Journal, vol. 38, no. 2, pp. 63-72, 2004. Crossref, https://doi.org/10.4031/002533204787522848
[17] Song Y. K, Lee C. M, Koo I. M, Trong D. T, Moon H and Choi H. R, “Development of Wall Climbing Robotic System for Inspection Purpose,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1990-1995, 2008. Crossref, https://doi.org/10.1109/IROS.2008.4650885