End-effector tracking for a mobile manipulator is achieved through Sensor Fusion techniques, implemented with a particular visual-inertial sensor suite and an Extended Kalman Filter algorithm. The suite is composed of an Optitrack motion capture system and a Honeywell HG4930 MEMS IMU, for which a further analysis on the mathematical noise model is reported. The filter is constructed in such a way that its complexity remains constant and independent of the visual algorithm, with the possibility of inserting additional sensors, to further improve the estimation accuracy. Experiments in real-time have been performed with the 12-DOF KUKA VALERI robot, extracting the position and the orientation of the end-effector and comparing their estimates with pure sensor measurements. Along with the physical results, issues related to calibration, working frequency and physical mounting are described.

KALMAN FILTER BASED SENSOR FUSION FOR A MOBILE MANIPULATOR / Ubezio, Barnaba; Sharma, Shashank; Van der Meer, Guglielmo; Taragna, Michele. - ELETTRONICO. - (2019). ((Intervento presentato al convegno ASME 2019 International Design Engineering Technical Conferences and Computers and Informationin Engineering Conference IDETC/CIE 2019 tenutosi a Anaheim, CA, USA nel August 18-21, 2019.

KALMAN FILTER BASED SENSOR FUSION FOR A MOBILE MANIPULATOR

UBEZIO, BARNABA;Taragna Michele
2019

Abstract

End-effector tracking for a mobile manipulator is achieved through Sensor Fusion techniques, implemented with a particular visual-inertial sensor suite and an Extended Kalman Filter algorithm. The suite is composed of an Optitrack motion capture system and a Honeywell HG4930 MEMS IMU, for which a further analysis on the mathematical noise model is reported. The filter is constructed in such a way that its complexity remains constant and independent of the visual algorithm, with the possibility of inserting additional sensors, to further improve the estimation accuracy. Experiments in real-time have been performed with the 12-DOF KUKA VALERI robot, extracting the position and the orientation of the end-effector and comparing their estimates with pure sensor measurements. Along with the physical results, issues related to calibration, working frequency and physical mounting are described.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2763472
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