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Image Based Visual Servoing through Nonlinear Model Predictive Control

Abstract : Image based visual servoing (IBVS) is a vision sensor based control architecture. In classical approach, an image Jacobian matrix maps image space errors into errors in Cartesian space. Then a simple proportional control law can be applied guaranteeing local convergence to a desired set point. One of the main advantage of IBVS is its robustness w.r.t camera and robot calibration errors and image measurement errors. Nevertheless, this scheme can not deal with nonlinear constraint such as joint limits and actuator saturation. Visibility constraint is not ensured with classical IBVS. A new IBVS scheme based on Nonlinear Model Predictive Control (NMPC) is proposed considering the direct dynamic model of the robot, its joint and torque limits, the camera projection model and the visibility constraint. Simulations exhibit the efciency and the robustness of the proposed solution to control a 6 degrees of freedom mechanical system.
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Conference papers
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Contributor : Philippe Poignet <>
Submitted on : Friday, January 19, 2007 - 4:32:44 PM
Last modification on : Saturday, June 19, 2021 - 3:01:37 AM


  • HAL Id : lirmm-00125467, version 1


Mickaël Sauvée, Philippe Poignet, Etienne Dombre, Estelle Courtial. Image Based Visual Servoing through Nonlinear Model Predictive Control. CDC'06: 45th International Conference on Decision and Control, Dec 2006, San Diego, CA, United States. ⟨lirmm-00125467⟩



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