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Hybrid tracking of human operators using IMU/UWB data fusion by a Kalman filter

By Juan Antonio Corrales Ramón, Francisco A. Candelas-Herías and Fernando Torres Medina


The precise localization of human operators in robotic workplaces is an important requirement to be satisfied in order to develop human-robot interaction tasks. Human tracking provides not only safety for human operators, but also context information for intelligent human-robot collaboration. This paper evaluates an inertial motion capture system which registers full-body movements of an user in a robotic manipulator workplace. However, the presence of errors in the global translational measurements returned by this system has led to the need of using another localization system, based on Ultra-WideBand (UWB) technology. A Kalman filter fusion algorithm which combines the measurements of these systems is developed. This algorithm unifies the advantages of both technologies: high data rates from the motion capture system and global translational precision from the UWB localization system. The developed hybrid system not only tracks the movements of all limbs of the user as previous motion capture systems, but is also able to position precisely the user in the environment.This work is funded by the Spanish Ministry of Education and Science through the research project ‘Design, Implementation and Experimentation of Intelligent Manipulation Scenarios for Automatic Assembly and Disassembly Applications’ (DPI2005-06222) and the pre-doctoral grant AP2005-1458. The Valencian Government has also funded this research through the project ‘infraestructura05/053’

Topics: Motion capture, Inertial sensors, UWB, Human tracking and monitoring, Indoor location, Data fusion, Kalman filter, Ingeniería de Sistemas y Automática
Publisher: Association for Computing Machinery
Year: 2008
DOI identifier: 10.1145/1349822.1349848
OAI identifier:

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