An algorithm for the estimation of the position and orientation of a moving object using a hybrid eye-in-hand/eye-to-hand multi-camera system is presented. Based on the extended Kalman filter, this approach exploits the data provided by all the cameras without "a priori" discrimination, allowing real-time estimation. The proposed formulation can be used with different kinds of image features and different representations of the object orientation. A simulation case study is reported to test the feasibility and the effectiveness of the proposed technique. ©2006 IEEE.

3D pose estimation for robotic applications based on a multi-camera hybrid visual system

LIPPIELLO, VINCENZO;SICILIANO, BRUNO;VILLANI, LUIGI
2006

Abstract

An algorithm for the estimation of the position and orientation of a moving object using a hybrid eye-in-hand/eye-to-hand multi-camera system is presented. Based on the extended Kalman filter, this approach exploits the data provided by all the cameras without "a priori" discrimination, allowing real-time estimation. The proposed formulation can be used with different kinds of image features and different representations of the object orientation. A simulation case study is reported to test the feasibility and the effectiveness of the proposed technique. ©2006 IEEE.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/476083
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