Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-05T12:16:57.925Z Has data issue: false hasContentIssue false
  • English
  • Français

Design, Modeling, and Control of a New Manipulating Climbing Robot Through Infrastructures Using Adaptive Force Control Method

Published online by Cambridge University Press:  14 January 2020

V. Boomeri Open the ORCID record for V. Boomeri [Opens in a new window]  and
H. Tourajizadeh Open the ORCID record for H. Tourajizadeh [Opens in a new window]
V. Boomeri
Affiliation:
Mechanical Engineering Department, Faculty of Engineering, Kharazmi University, Tehran, Iran E-mail: [email protected]
H. Tourajizadeh*
Affiliation:
Mechanical Engineering Department, Faculty of Engineering, Kharazmi University, Tehran, Iran E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

In this paper, design, modeling, and control of a grip-based climbing robot are performed, which consists of a triangular chassis and three actuating legs. This robot can climb through any trusses, pipeline, and scaffolds structures and can perform any inspectional and operational tasks in the high height which decreases the falling danger of operation and increases the safety of the workers. The proposed robot can be substituted for the workers to decrease the risk of death danger and increase the safety of the operation. Since these kinds of infrastructures are truss shaped, the traditional wheel-based climbing robots are not able to travel through these structures. Therefore, in this paper, a grip-based climbing robot is designed to accomplish the climbing process through the trusses and infrastructures in order to perform inspecting and manipulating tasks. Hence, a proper mechanism for the mentioned robot is designed and its related kinematic and kinetic models are developed. Robot modeling is investigated for two different modes including climbing and manipulating phases. Considering the redundancy of the proposed robot and the parallel mechanism employed in it, the active joints are selected in a proper way and its path planning is performed to accomplish the required missions. Concerning the climbing mode, the required computed torque method (CTM) is calculated by the inverse dynamics of the robot. However, for the manipulation mode, after path planning, two controlling strategies are employed, including feedback linearization (FBL) and adaptive force control, and their results are compared as well. It is shown that the latter case is preferable since the external forces implemented on the end effector tool is not exactly predetermined and thus, the controller should adapt the robot with the exerted force pattern of the manipulator. The modeling correctness is investigated by performing some analytic and comparative simulation scenarios in the MATLAB and comparing the results with the MSC-ADAMS ones, for both climbing and manipulating phases. The efficiency of the designed controller is also proved by implementing an unknown force pattern on the manipulator to check its efficiency toward estimating the mentioned implemented forces and compensating the errors. It is shown that the designed robot can successfully climb through a truss and perform its operating task by the aid of the employed adaptive controller in an accurate way.

Keywords

Climbing robotManipulationHybrid robotModelingAdaptive force control
Type
Articles
Information
Robotica , Volume 38 , Issue 11 , November 2020 , pp. 2039 - 2059
Copyright
Copyright © Cambridge University Press 2020

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

Balaguer, C., Gimenez, A. and Jardón, A., “Climbing robots’ mobility for inspection and maintenance of 3D complex environments,” Auton. Robots. 18(2), 157–169 (2005).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. Mech. 18(6) 1787–1798 (2013).CrossRefGoogle Scholar
Abderrahim, M., Balaguer, C., Giménez, A., Pastor, J. M. and Padron, V., “ROMA: A Climbing Robot for Inspection Operations,” Proceedings of the 1999 IEEE International Conference on Robotics and Automation, Michigan, USA (1999) pp. 2303–2308.Google Scholar
Tavakoli, M., Marjovi, A., Marques, L. and de Almeida, A. T., “3DCLIMBER: A Climbing Robot for Inspection of 3D Human Made Structures,” IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2008, Nice, France (2008) pp. 4130–4135.Google Scholar
Yun, S.-K. and Rus, D., “Optimal self assembly of modular manipulators with active and passive modules,” Auton. Robots 31(2–3), 183 (2011).CrossRefGoogle Scholar
Haynes, G. C., Khripin, A., Lynch, G., Amory, J., Saunders, A., Rizzi, A. A. and Koditschek, D. E., “Rapid Pole Climbing with a Quadrupedal Robot,” IEEE International Conference on Robotics and Automation, ICRA 2009, Kobe, Japan (2009) pp. 2767–2772.Google Scholar
Almonacid, M., Saltaren, R. J., Aracil, R. and Reinoso, O., “Motion planning of a climbing parallel robot,” IEEE Trans. Robot. Autom. 19(3), 485–489 (2003).CrossRefGoogle Scholar
Fauroux, J.-C. and Morillon, J., “Design of a Climbing Robot for Cylindro-Conic Poles Based on Rolling Self-Locking,” Mobile Robotics: Solutions and Challenges, World Scientific (2010) pp. 447–454.Google Scholar
Guan, Y., Jiang, L., Zhu, H., Wu, W., Zhou, X., Zhang, H. and Zhang, X., “Climbot: A bio-inspired modular biped climbing robot—system development, climbing gaits, and experiments,” J. Mech. Robot. 8(2) (2016) 021026.CrossRefGoogle Scholar
Tavakoli, M., Zakerzadeh, M. R., Vossoughi, G. and Bagheri, S., “A hybrid pole climbing and manipulating robot with minimum DOFs for construction and service applications,” Indust. Robot: Int. J. 32(2), 171–178 (2005).CrossRefGoogle Scholar
Baghani, A., Ahmadabadi, M. N. and Harati, A., “Kinematics Modeling of a Wheel-Based Pole Climbing Robot (UT-PCR),” Proceedings of the 2005 IEEE International Conference on Robotics and Automation, ICRA 2005, Barcelona, Spain (2005) pp. 2099–2104.Google Scholar
Bhole, A., Turlapati, S. H., Rajashekhar, V., Dixit, J., Shah, S. V. and Krishna, K. M., “Design of a robust stair-climbing compliant modular robot to tackle overhang on stairs,” Robotica 37(3), 428–444 (2019).CrossRefGoogle Scholar
Sunada, C., Argaez, D., Dubowsky, S. and Mavroidis, C., “A Coordinated Jacobian Transpose Control for Mobile Multi-Limbed Robotic Systems,” Proceedings of the 1994 IEEE International Conference on Robotics and Automation, San Diego, CA, USA (1994) pp. 1910–1915.Google Scholar
Bevly, D. M., Farritor, S. and Dubowsky, S., “Action module planning and its application to an experimental climbing robot,” Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2000, San Francisco, CA, USA (2000) pp. 4009–4014.Google Scholar
Korayem, M., Shafei, A. and Shafei, H., “Dynamic modeling of nonholonomic wheeled mobile manipulators with elastic joints using recursive Gibbs–Appell formulation,” Scientia Iranica 19(4), 1092–1104 (2012).CrossRefGoogle Scholar
Beji, L. and Pascal, M., “The kinematics and the full minimal dynamic model of a 6-DOF parallel robot manipulator,” Nonlin. Dynam. 18(4), 339–356 (1999).CrossRefGoogle Scholar
Li, Y. and Staicu, S., “Inverse dynamics of a 3-PRC parallel kinematic machine,” Nonlin. Dynam. 67(2), 1031–1041 (2012).CrossRefGoogle Scholar
Abedinnasab, M. H. and Vossoughi, G., “Analysis of a 6-DOF redundantly actuated 4-legged parallel mechanism,” Nonlin. Dynam. 58(4), 611 (2009).CrossRefGoogle Scholar
Korayem, M. H., Nikoobin, A. and Azimirad, V., “Maximum load carrying capacity of mobile manipulators: Optimal control approach,” Robotica 27(1), 147–159 (2009).CrossRefGoogle Scholar
Korayem, M. and Nikoobin, A., “Maximum payload path planning for redundant manipulator using indirect solution of optimal control problem,” Int. J. Adv. Manuf. Technol. 44(7–8), 725 (2009).CrossRefGoogle Scholar
Korayem, M., Irani, M. and Nekoo, S. R., “Load maximization of flexible joint mechanical manipulator using nonlinear optimal controller,” Acta Astronautica 69(7–8), 458–469 (2011).CrossRefGoogle Scholar
Korayem, M. H., Nohooji, H. R. and Nikoobin, A., “Path planning of mobile elastic robotic arms by indirect approach of optimal control,” Int. J. Adv. Robot. Syst. 8(1), 10 (2011).CrossRefGoogle Scholar
Atkeson, C. G., An, C. H. and Hollerbach, J. M., “Estimation of inertial parameters of manipulator loads and links,” Int. J. Robot. Res. 5(3), 101–119 (1986).CrossRefGoogle Scholar
Slotine, J.-J. E. and Li, W., “On the adaptive control of robot manipulators,” Int. J. Robot. Res. 6(3), 49–59 (1987).CrossRefGoogle Scholar
Shang, W.-W., Cong, S. and Ge, Y., “Adaptive computed torque control for a parallel manipulator with redundant actuation,” Robotica 30(3), 457–466 (2012).CrossRefGoogle Scholar
Yang, T.-C., Yang, J. C., and Kudva, P., “Load-adaptive control of a single-link flexible manipulator,” IEEE Trans. Syst. Man Cybern. 22(1), 85–91 (1992).CrossRefGoogle Scholar
Hayat, R., Leibold, M. and Buss, M., “Addressing control implementation issues in robotic systems using adaptive control,” Robotica 38(1), 171–184 (2020).CrossRefGoogle Scholar
Dubowsky, S., Sunada, C. and Mavroidis, C., “Coordinated motion and force control of multi-limbed robotic systems,” Auton. Robots. 6(1), 7–20 (1999).CrossRefGoogle Scholar
Bevly, D., Dubowsky, S. and Mavroidis, C., “A simplified Cartesian-computed torque controller for highly geared systems and its application to an experimental climbing robot,” J. Dyn. Syst. Measur. Control, 122(1), 27–32 (2000).CrossRefGoogle Scholar
Aoi, S. and Tsuchiya, K., “Locomotion control of a biped robot using nonlinear oscillators,” Auton. Robots 19(3), 219–232 (2005).CrossRefGoogle Scholar
Dong, S., “Gravity and inertial load adaptive control of wall-climbing robot,” J. Eng. 2019(13), 442–446 (2019).Google Scholar
Moon, J.-S. and Bae, J., “Gait optimization and energetics of ballistic walking for an underactuated biped with knees,” Nonlin. Dynam. 85(3), 1533–1546 (2016).CrossRefGoogle Scholar
Merlet, J.-P., Parallel Robots (Springer Science & Business Media, 2006).Google Scholar
Murray, R. M., A Mathematical Introduction to Robotic Manipulation (CRC Press, 2017).CrossRefGoogle Scholar
Slotine, J.-J.E. and Li, W., Applied Nonlinear Control (Prentice Hall, Englewood Cliffs, NJ, 1991).Google Scholar
Boomeri, V., Pourebrahim, S. and Tourajizadeh, H., “Kinematic and Dynamic Modeling of an Infrastructure Hybrid Climbing Robot,” 2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI), Tehran, Iran (2017) pp. 0834–0842.Google Scholar