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Modeling and validation of a novel tracked robot via multibody dynamics

Published online by Cambridge University Press:  24 July 2023

Andrea Grazioso ,
Angelo Ugenti ,
Rocco Galati ,
Giacomo Mantriota  and
Giulio Reina Open the ORCID record for Giulio Reina [Opens in a new window]
Andrea Grazioso
Affiliation:
Department of Mechanics, Mathematics, and Management, Politechnic University of Bari, Bari, Italy
Angelo Ugenti
Affiliation:
Department of Mechanics, Mathematics, and Management, Politechnic University of Bari, Bari, Italy
Rocco Galati
Affiliation:
Department of Mechanics, Mathematics, and Management, Politechnic University of Bari, Bari, Italy
Giacomo Mantriota
Affiliation:
Department of Mechanics, Mathematics, and Management, Politechnic University of Bari, Bari, Italy
Giulio Reina*
Affiliation:
Department of Mechanics, Mathematics, and Management, Politechnic University of Bari, Bari, Italy
*
Corresponding author: Giulio Reina; Email: giulio.reina@poliba.it
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Abstract

This article focuses on a multibody model of a new passive articulated suspension tracked robot. The model of the vehicle is developed using the multibody software MSC Adams (acronym for automatic dynamic analysis of mechanical systems) in conjunction with the Adams Tracked Vehicle toolkit. The various subsystems that make up the vehicle assembly are described, with particular attention to the modeling strategies of the swing arms that constitute the suspension system and the characterization of the track belt. The multibody model allows the system performance to be evaluated in advance for fine-tuning of the design parameters and using different configurations, for example, with active and locked suspension. Efforts are also presented to validate the multibody twin against the real prototype, showing a good agreement with field experiments. Once validated, the digital twin is used to assess the performance of the innovative suspension system in various challenging environments.

Keywords

multibody modeling and simulationrough-terrain mobile robotselectric unmanned vehiclestracked robotspassive articulated suspension
Type
Research Article
Information
Robotica , Volume 41 , Issue 10 , October 2023 , pp. 3211 - 3232
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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References

Rasool, R. H. and S, “Improving the tractive performance of walking tractors using rubber tracks,” Biosyst. Eng. 167, 51–62 (2018).CrossRefGoogle Scholar
Wong, J. and Huang, W., “‘Wheels vs. tracks’–A fundamental evaluation from the traction perspective,” J. Terramechanics 43(1), 27–42 (2006).CrossRefGoogle Scholar
Murphy, R., “Activities of the rescue robots at the world trade center from 11-21 September 2001,” IEEE Robot. Autom. Mag. 99(3), 50–61 (2004).CrossRefGoogle Scholar
Galati, R., Mantriota, G. and Reina, G., “Design and development of a tracked robot to increase bulk density of flax fibers,” J. Mech. Robot. 13(5), 1–14 (2021).CrossRefGoogle Scholar
t. Grigore, L., Oncioiu, I., Priescu, I. and Joiţa, D., “Development and evaluation of the traction characteristics of a crawler EOD robot,” Appl. Sci. 11(9), 3757 (2021).CrossRefGoogle Scholar
Botta, A., Cavallone, P., Baglieri, L., Colucci, G., Tagliavini, L. and Quaglia, G., “A review of robots, perception, and tasks in precision agriculture,” Appl. Mech. 3(3), 830–854 (2022).CrossRefGoogle Scholar
Mcbride, W., Longoria, R. G. and Krotkov, E.. Measurement and prediction of the off-road mobility of small robotic ground vehicles. (2003).Google Scholar
Nagatani, K., Kiribayashi, S., Okada, Y., Tadokoro, S., Nishimura, T., Yoshida, T., Koyanagi, E. and Hada, Y.. Redesign of Rescue Mobile Robot Quince. In: 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, (2011) pp. 13–18.Google Scholar
Huff, J., Conyers, S. and Voyles, R., “Mothership – A Serpentine Tread/Limb Hybrid Marsupial Robot for USAR,” 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), (2012) pp. 1–7.Google Scholar
Kim, J., Kim, J. and Lee, D., “Mobile robot with passively articulated driving tracks for high terrainability and maneuverability on unstructured rough terrain: Design, analysis, and performance evaluation,” J. Mech. Sci. Technol. 32(11), 5389–5400 (2018).CrossRefGoogle Scholar
Li, L., Zang, Y., Shi, T., Lv, T. and Lin, F., “Design and dynamic simulation analysis of a wheel- track composite chassis based on RecurDyn,” World Electr. Veh. J. 13(1), 12 (2022).CrossRefGoogle Scholar
Galati, R., Mantriota, G. and Reina, G., “Robonav: An affordable yet highly accurate navigation system for autonomous agricultural robots,” Robotics 11(5), 99 (2022).CrossRefGoogle Scholar
Vulpi, F., Marani, R., Petitti, A., Reina, G. and Milella, A., “An RGB-D multi-view perspective for autonomous agricultural robots,” Comput. Electron. Agric. 13, 107419 (2022).CrossRefGoogle Scholar
Ugenti, A., Galati, R., Mantriota, G. and Reina, G., “Analysis of an all-terrain tracked robot with innovative suspension system,” Mech. Mach. Theory 182, 105237 (2023).CrossRefGoogle Scholar
Grazioso, A., Galati, R., Mantriota, G. and Reina, G., “Multibody Simulation of a Novel Tracked Robot with Innovative Passive Suspension,” In: Advances in Italian Mechanism Science (Niola, V., Gasparetto, A., Quaglia, G. and Carbone, G., eds.) Springer International Publishing, Cham, (2022) pp. 139–146.CrossRefGoogle Scholar
Balena, M., Mantriota, G. and Reina, G., “Dynamic handling characterization and set-up optimization for a formula SAE race car via multi-body simulation,” Machines 9(6), 126 (2021).CrossRefGoogle Scholar
Blanco-Claraco, J., Leanza, A. and Reina, G., “A general framework for modeling and dynamic simulation of multibody systems using factor graphs,” Nonlinear Dyn. 105(3), 2031–2053 (2021).CrossRefGoogle Scholar
Adams Development Team. MSC Adams/view manual. (2022b). Accessed 05 December 2022.Google Scholar
Adams Development Team. MSC Adams/Adams tracked vehicle (ATV) toolkit. (2022a). Accessed 05 December 2022.Google Scholar
Jalon, J. D. and Bayo, E.. Kinematic and Dynamic Simulation of Multibody Systems (Springer, New York, NY, USA, 1994).CrossRefGoogle Scholar
Madsen, J., Heyn, T. and Negrut, D.. Methods for Tracked Vehicle System Modeling and Simulation (University of Wisconsin, Madison, 2010).Google Scholar
Nicolini, A., Mocera, F. and Soma, A., “Multibody simulation of a tracked vehicle with deformable ground contact model,” Proc. Inst. Mech. Eng. K: J. Multi-body Dyn. 233(1), 152–162 (2019).Google Scholar
Vasileiou, C., Smyrli, A., Drogosis, A. and Papadopoulos, E., “Development of a passive biped robot digital twin using analysis, experiments, and a multibody simulation environment,” Mech. Mach. Theory 163(1), 104346 (2021).CrossRefGoogle Scholar
ISO-8608:1995. Mechanical vibration-road surface profiles reporting of measured data. (1995).Google Scholar
Reina, G., Leanza, A. and Messina, A., “On the vibration analysis of off-road vehicles: Influence of terrain deformation and irregularity,” J. Vib. Control 24(22), 5418–5436 (2018).CrossRefGoogle Scholar