Adaptive Vision based Tracking Control of Robots with Uncertainty in Depth Information - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2007

Adaptive Vision based Tracking Control of Robots with Uncertainty in Depth Information

Abstract

In this paper, a vision based tracking controller with adaptation to uncertainty in depth information is presented. Depth uncertainty plays a special role in visual tracking 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 visual tracking task in presence of uncertainties in depth information, robot kinematics and dynamics. Simulation results are presented to illustrate the performance of the proposed controller.
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Dates and versions

lirmm-00366218 , version 1 (06-03-2009)

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Chien Chern Cheah, Chao Liu, Jean-Jacques E. Slotine. Adaptive Vision based Tracking Control of Robots with Uncertainty in Depth Information. ICRA: International Conference on Robotics and Automation, Apr 2007, Roma, Italy. pp.2817-2822, ⟨10.1109/ROBOT.2007.363898⟩. ⟨lirmm-00366218⟩
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