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A Generalized Vision-based Stiffness Controller for Robot Manipulators with Bounded Inputs

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Abstract

Generally, stiffness and impedance control schemes require knowledge of the location of any object with which a robot interacts within its workspace; therefore, the integration of a computer vision system within the control loop allows us to know the location of the robot end effector and the object (target) simultaneously. In this paper, a generalized and saturating vision-based stiffness controller with adaptive gravity compensation is presented. The proposed control algorithm is designed to regulate robot-environment interaction in task-space, where the contact force is modeled as a vector of generalized bounded spring-like forces. In order to control nonredundant robots, the proposed controller has a nonlinear proportional-derivative structure with static model-based compensation of gravitational forces, as it includes a regressor-based adaptive term. To support the proposal, the Lyapunov stability analysis of the closed-loop equilibrium vector is presented. Finally, the suitable performance of the proposed scheme was verified by numerical simulations and experimental tests.

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Authors and Affiliations

  1. Faculty of Science, Autonomous University of San Luis Potosi, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosi, SLP, 78295, Mexico

    Carlos Vidrios-Serrano, Marco Mendoza, Isela Bonilla & Berenice Maldonado-Fregoso

Authors
  1. Carlos Vidrios-Serrano
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  2. Marco Mendoza
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  3. Isela Bonilla
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  4. Berenice Maldonado-Fregoso
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Corresponding author

Correspondence to Marco Mendoza.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Yangmin Li under the direction of Myo Taeg Lim. This was work was supported by the Autonomous University of San Luis Potosi (C19-FAI-05-58.58) and the National Council for Science and Technology of Mexico (Grants 707604 and 707689).

Carlos Vidrios-Serrano received his B.E. and M.Sc. degrees in electronic engineering from the Autonomous University of Nayarit (AUN) and the Autonomous University of San Luis Potosi (AUSLP), Mexico, in 2004 and 2014, respectively. He is currently a Ph.D. candidate at the Faculty of Science, AUSLP and a full professor at the AUN, Mexico. His research interests include visual servoing, robot control and rehabilitation robotics.

Marco Mendoza received his B.E. degree in communications and electronics from the University of Colima, Mexico, in 2003, an M.Sc. degree in electronics from the Autonomous University of Puebla, Mexico, in 2006, and a Ph.D. degree in electrical engineering from the Autonomous University of San Luis Potosi (AUSLP), Mexico, in 2011. He is currently a full professor of biomedical engineering at the Faculty of Science, AUSLP, Mexico. His research interests include robot control and biorobotics.

Isela Bonilla received her B.E. degree in communications and electronics from the University of Colima, Mexico, in 2003, an M.Sc. degree in electronics from the Autonomous University of Puebla, Mexico, in 2006, and a Ph.D. degree in electrical engineering from the Autonomous University of San Luis Potosi (AUSLP), in 2011. She is currently a full professor of electronics at the Faculty of Science, AUSLP, Mexico. Her research interests include robot control and rehabilitation robotics.

Berenice Maldonado-Fregoso received her B.E. degree in control and computation from the Autonomous University of Nayarit, Mexico, in 2009, and an M.Sc. degree in electronic engineering from the Autonomous University of San Luis Potosi (AUSLP), Mexico, in 2014. She is currently a Ph.D. candidate at the Faculty of Science, AUSLP, Mexico. Her research interests include robot control and rehabilitation robotics.

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Vidrios-Serrano, C., Mendoza, M., Bonilla, I. et al. A Generalized Vision-based Stiffness Controller for Robot Manipulators with Bounded Inputs. Int. J. Control Autom. Syst. 19, 548–561 (2021). https://doi.org/10.1007/s12555-019-1056-7

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  • DOI: https://doi.org/10.1007/s12555-019-1056-7

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