Kalman filtering for sensor fusion in a human tracking system

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/14233
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Title: Kalman filtering for sensor fusion in a human tracking system
Authors: Corrales Ramón, Juan Antonio | Candelas-Herías, Francisco A. | Torres, Fernando
Research Group/s: Automática, Robótica y Visión Artificial
Center, Department or Service: Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal
Keywords: Kalman filter | Sensor fusion | Motion capture | Human-robot interaction | Human tracking | UWB localization
Knowledge Area: Ingeniería de Sistemas y Automática
Date Created: 1-May-2010
Issue Date: 1-May-2010
Publisher: INTECH | Sciyo
Citation: CORRALES RAMÓN, Juan Antonio; CANDELAS HERÍAS, Francisco Andrés; TORRES MEDINA, Fernando. "Kalman filtering for sensor fusion in a human tracking system". En: Kalman Filter / Edited by Vedran Kordic. Vukovar, Croatia : INTECH, 2010. ISBN 978-953-307-094-0, pp. 59-72
Abstract: This chapter presents a human tracking system for developing human-robot interaction tasks. This system is composed by two subsystems: an inertial motion capture system and a Ultra-WideBand (UWB) localization system. Two fusion algorithms are used to combine the measurements of both systems. The first fusion algorithm transforms measurements from the two systems in the same coordinate system by recalculating the transformation matrix each time a new measurement from the UWB system is received. This approach relies heavily on the accuracy of the measurements from the UWB system because the transformation matrix recalculation assumes that the last UWB measurement is completely correct. Thus, errors in UWB measurements are not considered and only the translational errors of the motion capture system are corrected. The second algorithm takes into account UWB errors and overcomes the drawbacks of the first approach by adding a modified Kalman filter.
Sponsor: This work is supported by the Spanish Ministry of Education and Science (MEC) under the research project DPI2005-06222 ('Design, Implementation and Experimentation of Intelligent Manipulation Scenarios for Automatic Assembly and Disassembly Applications') and the pre-doctoral grant AP2005-1458.
URI: http://hdl.handle.net/10045/14233
ISBN: 978-953-307-094-0
Language: eng
Type: info:eu-repo/semantics/bookPart
Peer Review: si
Publisher version: http://sciyo.com/articles/show/title/kalman-filtering-for-sensor-fusion-in-a-human-tracking-system
Appears in Collections:INV - AUROVA - Capítulos de Libros

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