GPS and IMU Fusion for Human Gait Estimation
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Authors
Steckenrider, J. Josiah
Crawford, Brock
Zheng, Penny
Issue Date
2021
Type
proceedings-article
Language
Keywords
Measurement units , Fuses , Sensor fusion , Real-time systems , Frequency estimation , Trajectory , Sensors
Alternative Title
Abstract
This paper proposes a framework for fusing information coming from an independent inertial measurement unit (IMU) and global positioning system (GPS) to deliver robust estimation of human gait. Because these two sensors provide very different kinds of data at different scales and frequencies, a novel approach which fuses global trajectory estimates and back-propagates this information to correct step vectors is put forth here. In several high-fidelity simulations, the proposed technique is shown to improve step estimation error up to 40% in comparison with an IMU-only approach. This work has implications for not only in-the-field biomechanics research, but also cooperative field robotic systems where it may be critical to accurately monitor a person’s position and state in real-time.
Description
Citation
J. J. Steckenrider, B. Crawford and P. Zheng, "GPS and IMU Fusion for Human Gait Estimation," 2021 IEEE 24th International Conference on Information Fusion (FUSION), Sun City, South Africa, 2021, pp. 1-7, doi: 10.23919/FUSION49465.2021.9627008.
Publisher
IEEE