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...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Buchanan, R, Camurri, M, Dellaert, F, Fallon, M
Aineistotyyppi: Conference item
Kieli:English
Julkaistu: Journal of Machine Learning Research 2022