Adaptive Jacobian Vision Based Control for Robots with Uncertain Depth Information - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Automatica Year : 2010

Adaptive Jacobian Vision Based Control for Robots with Uncertain Depth Information

Abstract

This paper presents a simple vision based setpoint controller with adaptation to uncertainty in depth information. Depth uncertainty plays a special role in vision based control as it appears nonlinearly in the overall Jacobian matrix and hence cannot be adapted together with other uncertain kinematic parameters. We propose a novel parameter update law to update the uncertain parameters of the depth. It is proved that system stability can be guaranteed for the vision regulation task in presence of uncertainties in depth information, robot kinematics and dynamics. Simulation results are presented to illustrate the performance of the proposed controller.

Dates and versions

lirmm-00629327 , version 1 (05-10-2011)

Identifiers

Cite

Chien Chern Cheah, Chao Liu, Jean-Jacques E. Slotine. Adaptive Jacobian Vision Based Control for Robots with Uncertain Depth Information. Automatica, 2010, 46, pp.1228-1233. ⟨10.1016/j.automatica.2010.04.009⟩. ⟨lirmm-00629327⟩
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