Abstract
A Free Model Task Space Controller (FMTSC) is presented in this paper for an omnidirectional mobile manipulator. However, it is well known the difficulty to know the precsise details of the robotic system and commonly limited for the accuracy of the kinematic and dynamic model, the model based methods are not sufficient, so far. Therefore the use of available information like joints velocities and robot tip velocity allow to estimate the robot Jacobian matrix information, without any requirement of mathematical model. An adaptive Kalman filter is computed to estimate Jacobian to deal with the adaptive robot control in the task space. The control law is developed with the Jacobian estimate for Strong Tracking Kalman Filter (STKF) algortihm. The control algorithm is intended for nonlinear discrete-time system (robot) which provides adpative control gain for taks space controller, designed by Fuzzy Rules Emulated Network Adaptive Gain (FRENAG). The performance of the controller is validated with Kuka youBot mobile manipulator plataform experiments.
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Acknowledgments
The authors would like to thank CONACyT (Project number 257253) for the financial support through this work and Science Basic project Number: 285599) which is called “Toma de decisiones multiobjetivo para sistemas altamente complejos”. The first author thanks CONACyT for his PhD scholarship.
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Gómez, J., Treesatayapun, C., Morales, A. (2018). Free Model Task Space Controller Based on Adaptive Gain for Robot Manipulator Using Jacobian Estimation. In: Batyrshin, I., Martínez-Villaseñor, M., Ponce Espinosa, H. (eds) Advances in Computational Intelligence. MICAI 2018. Lecture Notes in Computer Science(), vol 11289. Springer, Cham. https://doi.org/10.1007/978-3-030-04497-8_22
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DOI: https://doi.org/10.1007/978-3-030-04497-8_22
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