Abstract
Uncertainty and non-linearity are two major factors that affect the path tracking performance of Mecanum-wheeled robot (MWR) in both open-loop and closed-loop control. Conventional control method i.e. via inverse kinematics equation usually involves assumptions and parametric values. This paper proposes a path tracking and optimization method—Linear Angle-to-Gain (LA-G) that is straightforward and intuitive, and capable to achieve decent path tracking performance. The propose method does not require the knowledge of wheel’s radius and MWR’s dimension to perform control. Experiments in path tracking with and without the proposed path optimizer are analyzed and compared in term of integral of absolute error (IAE) and integral of square error (ISE) with respect to reference path. The result shows that the proposed path optimizer successfully improves the tracking of 45° diagonal path under the presence of uncertainties and non-linearity.
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Acknowledgements
The authors would like to thank Motion Control Research Laboratory and Universiti Teknikal Malaysia Melaka for the provision of facilities, utilities and financial support with high impact PJP grant (PJP/2017/FKE/HI11/S01536).
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Keek, J.S., Loh, S.L., Chong, S.H. (2020). Path Tracking and Optimization for Mecanum-Wheeled Robot via Linear Angle-to-Gain (LA-G) Method. In: P. P. Abdul Majeed, A., Mat-Jizat, J., Hassan, M., Taha, Z., Choi, H., Kim, J. (eds) RITA 2018. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-8323-6_4
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DOI: https://doi.org/10.1007/978-981-13-8323-6_4
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