Hostname: page-component-745bb68f8f-s22k5 Total loading time: 0 Render date: 2025-01-08T05:43:51.612Z Has data issue: false hasContentIssue false
  • English
  • Français

Modelling, simulation and experimental validation of wheel and arm locomotion based wall-climbing robot

Published online by Cambridge University Press:  18 March 2022

Ravindra Singh Bisht Open the ORCID record for Ravindra Singh Bisht [Opens in a new window] ,
Pushparaj Mani Pathak Open the ORCID record for Pushparaj Mani Pathak [Opens in a new window]  and
Soraj Kumar Panigrahi Open the ORCID record for Soraj Kumar Panigrahi [Opens in a new window]
Ravindra Singh Bisht
Affiliation:
Robotics and Control Laboratory, Mechanical & Industrial Engineering Department, Indian Institute of Technology, Roorkee-247667, India Acoustics, Instrumentation & Mechanical Systems Group, CSIR-Central Building Research Institute, Roorkee-247667, India
Pushparaj Mani Pathak*
Affiliation:
Robotics and Control Laboratory, Mechanical & Industrial Engineering Department, Indian Institute of Technology, Roorkee-247667, India
Soraj Kumar Panigrahi
Affiliation:
Acoustics, Instrumentation & Mechanical Systems Group, CSIR-Central Building Research Institute, Roorkee-247667, India
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

This article presents modelling, simulation, and development of a wall-climbing robot based on coupled wheel and arm-type locomotion mechanism. The developed robot consists of two mobile modules connected with a robot arm mechanism. The actuation of the robot arm is inspired by inchworm locomotion, particularly during wall-to-wall transition, obstacle avoidance, and uneven surface locomotion. Easiness in the interchanging of wheel to arm and vice versa makes the robot more effective compared to previously developed wall-climbing robots. The kinematic and dynamic model for the proposed coupled wheel and arm locomotion concept has been established. A combination of particle swarm optimization (PSO) and proportional, integral, derivatives (PID) feedback control algorithm has been developed using MATLAB to simulate the different cases of robot motions. The developed prototype of the wall-climbing robot is used to verify the coupled wheel and arm locomotion concept in various wall climbing scenarios. The simulation and experimental findings show good comparisons and validate the model-based design of the wall-climbing robot.

Keywords

wheel and arm locomotioncoupled dynamic modellingtrajectory trackingmotion simulationinchworm locomotionexperimental trials
Type
Research Article
Information
Robotica , Volume 41 , Issue 2 , February 2023 , pp. 433 - 469
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Zhu, D., Yi, X., Wang, Y., Lee, K. M. and Guo, J., “A mobile sensing system for structural health monitoring: design and validation,” Smart Mater. Struct. 19(5), 055011 (2010).CrossRefGoogle Scholar
Nguyen, S. T. and La, H. M., “A climbing robot for steel bridge inspection,” J. Intell. Robot. Syst. 102(4), 1–21 (2021).CrossRefGoogle Scholar
Abdulkader, R. E., Veerajagadheswar, P., Lin, N. H., Kumaran, S., Vishaal, S. R. and Mohan, R. E., “Sparrow: A magnetic climbing robot for autonomous thickness measurement in ship hull maintenance,” J. Mar. Sci. Eng. 8(6), 469 (2020).Google Scholar
Chu, B., Jung, K., Han, C. S. and Hong, D., “A survey of climbing robots: locomotion and adhesion,” Int. J. Precis. Eng. Man. 11(4), 633–647 (2010).CrossRefGoogle Scholar
Schmidt, D. and Berns, K., “Climbing robots for maintenance and inspections of vertical structures—a survey of design aspects and technologies,” Robot. Auton. Syst. 61(12), 1288–1305 (2013).CrossRefGoogle Scholar
Koo, M., Trong, T. D., Moon, Y. H. L. H., Koo, J., Park, S. K. and Choi, H. R., “Development of wall climbing robot system by using impeller type adhesion mechanism,” J. Intell. Robot. Syst. 72(1), 57–72 (2013).CrossRefGoogle Scholar
Fujita, M., Ikeda, S., Fujimoto, T., Shimizu, T., Ikemoto, S. and Miyamoto, T., “Development of universal vacuum gripper for wall-climbing robot,” Adv. Robot. 32(6), 283–296 (2018).CrossRefGoogle Scholar
He, B., Xu, S., Zhou, Y. and Wang, Z., “Mobility properties analyses of a wall climbing hexapod robot,” J. Mech. Sci. Technol. 32(3), 1333–1344 (2018).CrossRefGoogle Scholar
Liu, Y. and Seo, T., “AnyClimb-II: Dry-adhesive linkage-type climbing robot for uneven vertical surfaces,” Mech. Mach. Theory 124(5), 197–210 (2018).CrossRefGoogle Scholar
Sabermand, V., Ghorbanirezaei, S. and Hojjat, Y., “Testing the application of free flapping foils (FFF) as a method to improve adhesion in an electrostatic wall-climbing robot,” J. Adhes. Sci. Technol. 33(23), 2579–2594 (2019).CrossRefGoogle Scholar
Guan, Y., Zhu, H., Wu, W., Zhou, X., Jiang, L., Cai, C., Zhang, L. and Zhang, H., “A modular biped wall-climbing robot with high mobility and manipulating function,” IEEE/ASME Trans. Mechatron. 18(6), 1787–1798 (2012).CrossRefGoogle Scholar
Tummala, R. L., Mukherjee, R., Xi, N., Aslam, D., Dulimarta, H., Xiao, J., Minor, M. and Dang, G., “Climbing the walls [robots],” IEEE Robot. Autom. Mag. 9(4), 10–19 (2002).CrossRefGoogle Scholar
Mazumdar, A. and Asada, H. H., “An underactuated, magnetic-foot robot for steel bridge inspection,” J. Mechan. Robot. 2(3), 031007 1–9 (2010).Google Scholar
Nam, S., Oh, J., Lee, G., Kim, J. and Seo, T., “Dynamic analysis during internal transition of a compliant multi-body climbing robot with magnetic adhesion,” J. Mech. Sci. Technol. 28(12), 5175–5187 (2014).CrossRefGoogle Scholar
Lee, G., Wu, G., Kim, J. and Seo, T., “High-payload climbing and transitioning by compliant locomotion with magnetic adhesion,” Robot. Auton. Syst. 60(10), 1308–1316 (2012).CrossRefGoogle Scholar
Lee, G., Kim, H., Seo, K., Kim, J., Sitti, M. and Seo, T., “Series of multilinked caterpillar track-type climbing robots,” J. Field Robot. 33(6), 737–750 (2016).CrossRefGoogle Scholar
Fan, J., Xu, T., Fang, Q., Zhao, J. and Zhu, Y., “A novel style design of a permanent-magnetic adsorption mechanism for a wall-climbing robot,” ASME J. Mech. Robot. 12(3), 118 (2020).CrossRefGoogle Scholar
Balaguer, C., Giménez, A., Pastor, J. M., Padron, V. M. and Abderrahim, M., “A climbing autonomous robot for inspection applications in 3d complex environments,” Robotica 18(3), 287–297 (2000).CrossRefGoogle Scholar
Tavakoli, M., Lourenço, J., Viegas, C., Neto, P. and de Almeida, A. T., “The hybrid omniclimber robot: wheel based climbing, arm based plane transition, and switchable magnet adhesion,” Mechatronics 36(3), 136–146 (2016).CrossRefGoogle Scholar
Wang, R. and Kawamura, Y., “Development of climbing robot for steel bridge inspection,” Ind. Robot Int. J. 43(4), 429–447 (2016).CrossRefGoogle Scholar
La, H. M., Dinh, T. H., Pham, N. H., Ha, Q. P. and Pham, A. Q., “Automated robotic monitoring and inspection of steel structures and bridges,” Robotica 37(5), 947–967 (2019).CrossRefGoogle Scholar
Myeong, W. and Myung, H., “Development of a wall-climbing drone capable of vertical soft landing using a tilt-rotor mechanism,” IEEE Access 7, 4868–4879 (2018).CrossRefGoogle Scholar
Hillenbrand, C., Schmidt, D. and Berns, K., “CROMSCI: development of a climbing robot with negative pressure adhesion for inspections,” Ind. Robot Int. J. 35(3), 228–237 (2008).CrossRefGoogle Scholar
Khan, M. B., Chuthong, T., Do, C. D., Thor, M., Billeschou, P., Larsen, J. C. and Manoonpong, P., “iCrawl: An inchworm-inspired crawling robot,” IEEE Access 8, 200655–200668 (2020).CrossRefGoogle Scholar
Bisht, R. S., Pathak, P. M. and Panigrahi, S. K., “Experimental investigations on permanent magnet based wheel mechanism for safe navigation of climbing robot,” Proc. Comput. Sci. 133(4), 377–384 (2018).CrossRefGoogle Scholar
Bisht, R. S., Pathak, P. M. and Panigrahi, S. K., “Development of Magnetic Adhesion based Wheel-Driven Climbing Machine for Ferrous Surface Applications,” In: ASME, 2018 Dynamic Systems and Control Conference (Atlanta, Georgia), 51890, V001T04A016(2018).Google Scholar
Huang, H., Li, D., Xue, Z., Chen, X., Liu, S., Leng, J. and Wei, Y., “Design and performance analysis of a tracked wall-climbing robot for ship inspection in shipbuilding,” Ocean Eng. 131(1), 224–230 (2017).CrossRefGoogle Scholar
Pagano, D. and Liu, D., “An approach for real-time motion planning of an inchworm robot in complex steel bridge environments,” Robotica 35(6), 1280–1309 (2017).CrossRefGoogle Scholar
Phipps, C. C., Shores, B. E. and Minor, M. A., “Design and quasi-static locomotion analysis of the rolling disk biped hybrid robot,” IEEE Trans. Robot. 24(6), 1302–1314 (2008).CrossRefGoogle Scholar
Nguyen, S. T., Pham, A. Q., Motley, C. and La, H. M., “A Practical Climbing Robot for Steel Bridge Inspection” In: IEEE International Conference on Robotics and Automation (ICRA 2020) (2020) pp. 9322 –9328.Google Scholar
Bisht, R. S., Pathak, P. M. and Panigrahi, S. K., A hybrid robotic device and method for climbing with multiple degrees of freedom, Indian Patent Office: 201911052507 (published), (2021).Google Scholar
Sarkar, N., Yun, X. and Kumar, V., “Control of mechanical systems with rolling constraints: application to dynamic control of mobile robots,” Int. J. Robot. Res. 13(1), 55–69 (1994).CrossRefGoogle Scholar
Yamamoto, Y. and Yun, X., “Effect of the dynamic interaction on coordinated control of mobile manipulators,” IEEE Trans. Robot. Autom. 12(5), 816–824 (1996).CrossRefGoogle Scholar
Fierro, R. and Lewis, F. L., “Control of a nonholonomic mobile robot: backstepping kinematics into dynamics,” J. Robot. Syst. 14(3), 149–163 (1997).3.0.CO;2-R>CrossRefGoogle Scholar
Yun, X. and Yamamoto, Y., “Stability analysis of the internal dynamics of a wheeled mobile robot,” J. Robot. Syst. 14(10), 697–709 (1997).3.0.CO;2-P>CrossRefGoogle Scholar
Kennedy, J. and Eberhart, R., “Particle Swarm Optimization,” In: Proceedings of ICNN’95-International Conference on Neural Networks (IEEE, 1995) 1942–1948.Google Scholar
Fister, D., Fister, J. I., Fister, I. and Šafarič, R., “Parameter tuning of PID controller with reactive nature-inspired algorithms,” Robot. Auton. Syst. 84(1), 64–75 (2016).CrossRefGoogle Scholar
Bisht, R. S., Pathak, P. M. and Panigrahi, S. K., “Design and development of a glass façade cleaning robot,” Mech. Mach. Theory 168(2), 104585 (2022).CrossRefGoogle Scholar
Samanta, B. and Nataraj, C., “Use of particle swarm optimization for machinery fault detection,” Eng. Appl. Artif. Intel. 22(2), 308–316 (2009).CrossRefGoogle Scholar
Espinoza, R. V., de Oliveira, A. S., de Arruda, L. V. R. and Junior, F. N., “Navigation’s stabilization system of a magnetic adherence-based climbing robot,” J. Intell. Robot. Syst. 78(1), 65–81 2015 (2015).CrossRefGoogle Scholar