Learning inertial odometry for dynamic legged robot state estimation
This paper introduces a novel proprioceptive state estimator for legged robots based on a learned displacement measurement from IMU data. Recent research in pedestrian tracking has shown that motion can be inferred from inertial data using convolutional neural networks. A learned inertial displaceme...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2022
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