TY - GEN
T1 - Efficient integrity monitoring for KF-based localization
AU - Arana, Guillermo Duenas
AU - Joerger, Mathieu
AU - Spenko, Matthew
N1 - Funding Information:
This work was supported by NSF Grant #1637899
Funding Information:
*This work was supported by NSF Grant #1637899 1G. D. Arana, student member IEEE, and M. Spenko, member IEEE, are with the Mechanical, Materials and Aerospace Engineering Dept., Illinois Institute of Technology, Chicago, IL, USA [email protected] 2M. Joerger, member IEEE, is with the Dept. of Aerospace and Mechanical Engineering, University of Arizona, Tucson, AZ, USA
Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - This paper presents a new method to efficiently monitor localization safety in mobile robots. Localization safety is quantified by measuring the system's integrity risk, which is a well-known aviation performance metric. However, aviation integrity monitoring solutions almost exclusively rely on the Global Navigation Satellite System (GNSS) while robot navigation usually needs the additional information provided by a state evolution model and/or relative positioning sensors, which makes previously established approaches impractical. In response, this paper develops an efficient integrity monitoring methodology applicable to Kalman Filter-based localization. The work is intended for life-or mission-critical operations such as co-robot applications where ignoring the impact of faults can jeopardize human safety.
AB - This paper presents a new method to efficiently monitor localization safety in mobile robots. Localization safety is quantified by measuring the system's integrity risk, which is a well-known aviation performance metric. However, aviation integrity monitoring solutions almost exclusively rely on the Global Navigation Satellite System (GNSS) while robot navigation usually needs the additional information provided by a state evolution model and/or relative positioning sensors, which makes previously established approaches impractical. In response, this paper develops an efficient integrity monitoring methodology applicable to Kalman Filter-based localization. The work is intended for life-or mission-critical operations such as co-robot applications where ignoring the impact of faults can jeopardize human safety.
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U2 - 10.1109/ICRA.2019.8794362
DO - 10.1109/ICRA.2019.8794362
M3 - Conference contribution
AN - SCOPUS:85071507121
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 6374
EP - 6380
BT - 2019 International Conference on Robotics and Automation, ICRA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Robotics and Automation, ICRA 2019
Y2 - 20 May 2019 through 24 May 2019
ER -