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), pp. 2732-2737. (Intervento presentato al convegno IEEE International Conference on Robotics and Automation tenutosi a Orlando, FL nel May) [10.1109/ROBOT.2006.1642114].
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
