Hostname: page-component-76fb5796d-25wd4 Total loading time: 0 Render date: 2024-04-25T13:49:47.165Z Has data issue: false hasContentIssue false
  • English
  • Français

Influence of CNT-based Nanocomposites in Dynamic Performance of Redundant Articulated Robot

Published online by Cambridge University Press:  30 April 2020

M. Saravana Mohan Open the ORCID record for M. Saravana Mohan [Opens in a new window]  and
P. S. Samuel Ratna Kumar
M. Saravana Mohan*
Affiliation:
Dept. of Mechatronics Engineering, Kumaraguru College of Technology, Coimbatore, 641035, Tamil Nadu, India
P. S. Samuel Ratna Kumar
Affiliation:
Dept. of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore, 641035, Tamil Nadu, India
*
*Corresponding author. E-mail: saravana.moha@gmail.com
Get access Rights & Permissions [Opens in a new window]

Summary

In this study, AA5083-reinforced multiwalled carbon nanotubes (MWCNT) nanocomposites were selected as the alternate material for a redundant articulated robot (RAR) design by varying the composition of MWCNT wt%. By assigning AA5083-reinforced MWCNT as a custom material to the parts of RAR developed by Solid Works and exported to MATLAB/SimMechanics platform to convert the model into multi-body system blocks. The dynamic parameter torque was observed utilising simulation capability in a SimMechanics second-generation environment. The simulation results inferred that AA5083 reinforced with increased wt% of MWCNT has better properties suitable for RAR design.

Keywords

Redundant articulated robot (RAR)NanocompositesMWCNTDynamic performanceSolidWorksSimMechanicsMechanics explorer
Type
Articles
Information
Robotica , Volume 39 , Issue 1 , January 2021 , pp. 153 - 164
Copyright
Copyright © The Author(s) 2020. 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

Kiyoto, I., Hitonobu, K., Katsuyuki, K., Kenji, K., “Observation of wear surface between pure PEEK and counterpart materials; titanium and 7075 aluminum alloy, in robot joint,” App. Mech. Mater. 307, 347–351 (2013).Google Scholar
Dentler, D. R. II, Design, Control, and Implementation of a Three Link Articulated Robot Arm. Master’s Thesis (Dept. Mechanical. Eng. Akron (OH): The University of Akron, 2008).Google Scholar
Dai, G. L., Chang, S. L., Hak, G. L., Hui, Y. H. and Jong, W. K., “Novel applications of composite structures to robots, machine tools and automobiles,” Comp. Struc. 66(1–4), 17–39 (2004).Google Scholar
Dai, G. L., Kwang, S. J., Ki, S.K. and Yoon, K. K., “Development of the anthropomorphic robot with carbon fiber epoxy composite materials,” Comp. Struc. 25(1–4), 313–324 (1993).Google Scholar
Li, Q. and Christian, A., “CNT reinforced light metal composites produced by melt stirring and by high pressure die casting,” Comp. Sci. Tech. 70(16), 2242–2247 (2010).CrossRefGoogle Scholar
Thostenson, E. T., Li, C. and Chou, T. W., “Nanocomposites in context,” Comp. Sci. Tech. 65(3–4), 491–516 (2005).CrossRefGoogle Scholar
Li, C. and Chou, T. W., “Elastic moduli of multi-walled carbon nanotubes and the effect of van der Waals forces,” Comp. Sci. Tech. 63(11), 1517–1524 (2003).10.1016/S0266-3538(03)00072-1CrossRefGoogle Scholar
Kashyap, K. T. and Patil, R. G., “On Young’s modulus of multi-walled carbon nanotubes,” Bull. Mater. Sci. 31, 185–187 (2008).CrossRefGoogle Scholar
Esawi, A., Morsi, K. and Sayed, A., “Effect of carbon nanotube (CNT) content on the mechanical properties of CNT-reinforced aluminium composites,” Comp. Sci.Tech. 70(16), 2237–2241 (2010)CrossRefGoogle Scholar
Liu, Z. Y., Xu, S. J. and Xiao, B. L., “Effect of ball-milling time on mechanical properties of carbon nanotubes reinforced aluminium matrix composites,” Comp. Part A 43(12), 2161–2168 (2012).CrossRefGoogle Scholar
Liao, J. and Tan, M. J., “A simple approach to prepare Al/CNT composite: spread–dispersion (SD) method,” Mater. Let. 65(17–18), 2742–2744 (2011).CrossRefGoogle Scholar
Choi, H. J., Shin, J. H. and Bae, D. H., “The effect of milling conditions on microstructures and mechanical properties of Al/MWCNT composites,” Comp. Part A 43(7), 1061–1072, (2012).CrossRefGoogle Scholar
Shin, S. E. and Bae, D. H., “Strengthening behavior of chopped multi-walled carbon nanotube reinforced aluminum matrix composites,” Mater. Charac. 83, 170–177 (2013).CrossRefGoogle Scholar
Samuel Ratna Kumar, P. S., Robinson Smart, D.S. and John Alexis, S., “Corrosion behaviour of aluminium metal matrix reinforced with multi-wall carbon nanotube,” J. Asian Ceram. Soc. 5(1), 71–75, (2017).CrossRefGoogle Scholar
Chen, B. and Shen, J., “Solid-state interfacial reaction and load transfer efficiency in carbon nanotubes (CNTs)-reinforced aluminum matrix composites,” Carbon. 114, 198–208 (2017).CrossRefGoogle Scholar
Siciliano, B. and Khatib, O., Handbook of Robotics (Springer, Berlin, Heidelberg, 2008).10.1007/978-3-540-30301-5CrossRefGoogle Scholar
Patel, R. and Shadpey, F., Control of Redundant Robot Manipulators (Springer Verlag, Berlin, Heidelberg, 2005).Google Scholar
Maciejewski, A. and Klein, C. A., “Obstacle avoidance for kinematically redundant manipulators in dynamically varying environments,” Int. J. Robot. Res. 4(3), 109–119 (1985)CrossRefGoogle Scholar
Nakamura, Y., Hanafusa, H. and Yoshikawa, T., “Task-priority based redundancy control of robot manipulators,” Int. J. Robot. Res. 6(2), 3–15 (1987).CrossRefGoogle Scholar
Klein, C. A. and Blaho, B. E., “Dexterity measures for the design and control of kinematically redundant manipulators,” Int. J. Robot. Res. 6(2), 72–84 (1987).10.1177/027836498700600206CrossRefGoogle Scholar
Seraji, H., “Improved configuration control for redundant robots,” J. Robot. Syst. 7(6), 897–928 (1990).CrossRefGoogle Scholar
Maciejewski, A., “Kinetic limitations on the use of redundancy in robotic manipulators,” IEEE Trans. Robot. Autom. 7(2), 205–211 (1991).CrossRefGoogle Scholar
Potkonjak, V., “New approach to the application of redundant robots,” Robot. Comput. Integ. Manuf. 8(3), 181–185 (1991).10.1016/0736-5845(91)90019-OCrossRefGoogle Scholar
Chen, C. L. and Lin, C. J., “Motion planning of redundant robots,” J. Robot. Syst. 14(12), 839–850 (1997).3.0.CO;2-V>CrossRefGoogle Scholar
Vosniakos, G. C. and Kannas, Z., “Motion coordination for industrial robotic systems with redundant degrees of freedom,” Robot. Comput. Integ. Manuf. 25(2), 417–431 (2009).CrossRefGoogle Scholar
Michel, O., “Cyberbotics Ltd – WebotsTM: Professional mobile robot simulation,” Int. J. Adv. Robot. Syst. 1(1), 39–42 (2004).CrossRefGoogle Scholar
Zlajpah, L., “Simulation in robotics,” Math. Comput. Simulat. 79(4), 879–897 (2008).CrossRefGoogle Scholar
Sika, Z., Valasek, M., Bauma, V. and Ampola, T. V., “Design of redundant parallel robots by multidisciplinary virtual modeling,” In: Virtual Nonlinear Multibody Systems (Schiehlen, W. and Valasek, M., eds.) (Kluwer Academic Publishers, Dordrecht, 2003) pp. 233–241.CrossRefGoogle Scholar
Ionescu, F., “Modelling and simulation in mechatronics,” IFAC Proc. 40(18), 301–312 (2007).CrossRefGoogle Scholar
Hobarth, W., Gattringer, H. and Bremer, H., “A dynamic model for a hybrid articulated robot,” Proc. Appl. Math. Mech. 8(1) 10123–10124 (2008).CrossRefGoogle Scholar
Fleischera, J. and Kraußeb, M., “Physically consistent parameter optimization for the generation of pose independent simulation models using the example of a 6-axis articulated robot,” Procedia CIRP 12, 217–221 (2013).CrossRefGoogle Scholar
Almaged, M., “Forward and inverse kinematic analysis and validation of the ABB IRB 140 industrial robot,” Int. J. Electron. Mech. Mechatron. Eng. 7(2), 1383–1401 (2017).CrossRefGoogle Scholar
Wood, G. D. and Kennedy, D. C., Simulating Mechanical Systems in Simulink with SimMechanics (The MathWorks, Natick 2003). Available from: Math works [06 January 2016].Google Scholar
Shaoqiang, Y., Zhong, L. and Xingshan, L., “Modeling and Simulation of Robot Based on Matlab/SimMechanics.” Proceedings of the 27th Chinese Control Conference, Yunnan, China, (2008) pp. 161–165.Google Scholar
Wen, L. Z., Liang, Z. G., Ping, Z. W. and Bin, J., “A simulation platform design of humanoid robot based on SimMechanics and VRML,” Procedia Eng. 15, 215–219 (2011).Google Scholar
Fajar, M., Douglas, S. S. and Gomm, J. B., “Modelling and simulation of spherical inverted pendulum based on LQR control with SimMechanics,” Appl. Mech. Mater. 391, 163–167 (2013).CrossRefGoogle Scholar
Kutuk, M. E., Halicioglu, R. and Dulger, L. C., “Kinematics and simulation of a hybrid mechanism: MATLAB/SimMechanics,” J. Phys. Conf. Ser. 574, 451–458 (2015).CrossRefGoogle Scholar
Zi, B., Cao, J. and Zhu, Z., “Dynamic simulation of hybrid-driven planar five bar parallel mechanism based on SimMechanics and tracking control,” Int. J. Adv. Robot. Syst. 8(4), 28–33 (2011).10.5772/45683CrossRefGoogle Scholar
Liu, J., Gong, Y., Chen, G. and Chen, H., “Modeling and Simulation of Loader Working Device Based on SimMechanics,” International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), Changchun, China (2011) pp. 2054–2059.Google Scholar
Yu, L., Zhang, L., Zhang, N. and Yang, S., “Kinematics, simulation and analysis of 3-RPS parallel robot on SimMechanics,” Proc. IEEE Int. Conf. Inf. Autom. (2010) pp. 2363–2367.Google Scholar
Li, Y., Wang, X., Xu, P., Zheng, D., Liu, W., Wang, Y. and Qiao, H., “SolidWorks/SimMechanics Based Lower Extremity Exoskeleton Modeling Procedure for Rehabilitation,” World Congress on Medical Physics and Biomedical Engineering, IFMBE Proceedings (2013) pp. 2058–2061.Google Scholar
Yang, C., He, J., Han, J. and Liu, X., “Real-time state estimation for spatial six-degree-of-freedom linearly actuated parallel robots,” Mechatronics 19(6), 1026–1033 (2009).CrossRefGoogle Scholar
Hanchen, L., Xinhua, Z. and Haoliang, X., “Modelling and simulation of 3RRRT parallel manipulator based on MALTAB with SimMechanics,” Proc. Int. Forum Inf. Technol. App. (2009) pp. 290–293.Google Scholar
Gouasmi, M.,Ouali, M., Fernini, B. and Meghatria, M., “Kinematic modelling and simulation of a 2-R robot using SolidWorks and verification by MATLAB/Simulink,” Int. J. Adv. Robot. Syst. 9(6), 245 (2012).CrossRefGoogle Scholar
Saravanamohan, M. and Anbumalar, V., “Modelling and simulation of multi spindle drilling redundant SCARA robot using SolidWorks and MATLAB/SimMechanics,” RevistaFacultad de Ingeniería, 8(1), 63–72 (2016).Google Scholar
Gao, J., Wang, Y. and Chen, Z., “Modelling and simulation of inverse kinematics for planar 3-RRR parallel robot based on SimMechanics,” Adv. Mat. Res. 898, 510–513 (2014).Google Scholar
Gang, L. S., Wang, D. H., Cheng, W. S. and Nan, Z. Y., “Path planning and system simulation for an industrial spot welding robot based on SimMechanics,” Key Eng. Mat. 419-420, 665–668 (2010).Google Scholar
Udai, A. D., Rajeevlochana, C. G. and Saha, S.K., “Dynamic Simulation of a KUKA KR5 Industrial Robot Using MATLAB SimMechanics,” 15th National Conference on Machines and Mechanisms (NaCoMM) 2011, Chennai, India (2011) pp. 1–8.Google Scholar
Mineo, C., Pierce, S. G., Nicholson, P. I. and Cooper, I., “Robotic path planning for non-destructive testing – a custom MATLAB toolbox approach,” Robot. Comput. Integr. Manuf. 37, 1–12 (2016)CrossRefGoogle Scholar
Juan, W., He, S. Z., Xiang, Z. Z. and Rong, M. E., “Analysis and simulation of 6R robot in virtual reality,” IFAC Papers OnLine 49(16), 426–430 (2016).10.1016/j.ifacol.2016.10.078CrossRefGoogle Scholar
Adeyeri, M. K., Ayodeji, S. P. and Olasanoye, O., “Modelling and simulation of 4 DOF robotic arm for an automated Roselle tea processing plant using Solidwoks and Matlab Simulik,” IFAC PapersOnLine, 50(2), 249–250 (2017).CrossRefGoogle Scholar
Aburaia, M., Markl, E. and Stuja, K., “New concept for design and control of 4 axis robot using the additive manufacturing technology,” Procedia Eng. 100, 1364–1369 (2015).CrossRefGoogle Scholar