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Improving tracking trajectories with motion estimation

Authors: Jorge Pomares; Gabriel J. García; Fernando Torres Medina;

Improving tracking trajectories with motion estimation

Abstract

Up to now, different methods have been proposed to track trajectories using visual servoing systems. However, when these approaches are employed to track trajectories specified with respect to moving objects, different considerations must be included in the visual servoing formulation to progressively decrease the tracking error. This paper shows the main properties of a non-time dependent visual servoing system to track image trajectories. The control action obtained integrates the motion estimation of the object from which the features are extracted. The proposed motion estimator employs information from the measures of the extracted features and from the variation of the camera locations. These variations are obtained determining the Homography matrix between consecutive camera frames.

This work was funded by the Spanish MCYT project DPI2005-06222 “Diseño, implementación y experimentación de escenarios de manipulación inteligentes para aplicaciones de ensamblado y desensamblado automático” and by the project GV05/007: “Diseño y experimentación de estrategias de control visual-fuerza para sistemas flexibles de manipulación”.

Keywords

Visual control, Tracking trajectories, Motion estimation, Ingeniería de Sistemas y Automática

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green