TY  - CONF
A1  - Wöhle, Lukas
A1  - Miller, Stanislaw
A1  - Gerken, Jens
A1  - Gebhard, Marion
T1  - A Robust Interface for Head Motion based Control of a Robot Arm using MARG and Visual Sensors
T2  - 2018 IEEE International Symposium on Medical Measurements and Applications. June 11-13, 2018. Rome. 2018 symposium proceedings
N2  - Head-controlled human machine interfaces have gained popularity over the past years, especially in the restoration of the autonomy of severely disabled people, like tetraplegics. These interfaces need to be reliable and robust regarding the environmental conditions to guarantee safety of the user and enable a direct interaction between a human and a machine. This paper presents a hybrid MARG and visual sensor system for head orientation estimation which is in this case used to teleoperate a robotic arm. The system contains a Magnetic Angular Rate Gravity (MARG)-sensor and a Tobii eye tracker 4C. A MARG sensor consists of tri-axis accelerometer, gyroscope as well as a magnetometer which enable a complete measurement of orientation relative to the direction of gravity and magnetic field of the earth. The tri-axis magnetometer is sensitive to external magnetic fields which result in incorrect orientation estimation from the sensor fusion process. In this work the Tobii eye tracker 4C is used to increase head orientation estimation because it also features head tracking even though it is commonly used for eye tracking. This type of visual sensor does not suffer magnetic drift. However, it computes orientation data only, if a user is detectable. Within this work a state machine is presented which enables data fusion of the MARG and visual sensor to improve orientation estimation. The fusion of the orientation data of MARG and visual sensors enables a robust interface, which is immune against external magnetic fields. Therefore, it increases the safety of the human machine interaction.
KW  - sensor fusion
KW  - hybrid sensor system
KW  - Kalman filter
KW  - state machine
KW  - Zustandsmaschine
Y1  - 2018
UR  - https://whge.opus.hbz-nrw.de/frontdoor/index/index/docId/3185
SN  - 978-1-5386-3392-2
ER  -