Motion Tracking: No Silver Bullet, but a Respectable Arsenal
IEEE Computer Graphics and Applications
Hybrid Tracking for Outdoor Augmented Reality Applications
IEEE Computer Graphics and Applications
Inertial Head-Tracker Sensor Fusion by a Complimentary Separate-Bias Kalman Filter
VRAIS '96 Proceedings of the 1996 Virtual Reality Annual International Symposium (VRAIS 96)
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
A Study of Practical Approach of Using Motion Capture and Keyframe Animation Techniques
CGIV '04 Proceedings of the International Conference on Computer Graphics, Imaging and Visualization
A Flexible Software Architecture for Hybrid Tracking
Journal of Robotic Systems
An immersion-type 3D dynamic simulation environment for developing human interactive robot systems
Systems and Computers in Japan
Practical motion capture in everyday surroundings
ACM SIGGRAPH 2007 papers
Simple inexpensive interface for robots using the Nintendo Wii controller
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Sensor data integration for indoor human tracking
Robotics and Autonomous Systems
Safe human-robot interaction based on dynamic sphere-swept line bounding volumes
Robotics and Computer-Integrated Manufacturing
Toward a highly accurate ambulatory system for clinical gait analysis via UWB radios
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Proceedings of the Fifth International Conference on Body Area Networks
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
Journal of Intelligent and Robotic Systems
Proceedings of the 12th international conference on Information processing in sensor networks
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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.