Drift-free humanoid state estimation fusing kinematic, inertial and LIDAR sensing

Drift-free humanoid state estimation fusing kinematic, inertial and LIDAR sensing

This paper describes an algorithm for the probabilistic fusion of sensor data from a variety of modalities (inertial, kinematic and LIDAR) to produce a single consistent position estimate for a walking humanoid. Of specific interest is our approach for continuous LIDAR-based localization which maint...

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Bibliographic Details
Main Authors: Fallon, Maurice (Contributor), Antone, Matthew (Contributor), Roy, Nicholas (Contributor), Teller, Seth (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2016-11-21T15:47:03Z.
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