Search Results for author: David J. Yoon

Found 3 papers, 0 papers with code

Unsupervised Learning of Lidar Features for Use in a Probabilistic Trajectory Estimator

no code implementations22 Feb 2021 David J. Yoon, Haowei Zhang, Mona Gridseth, Hugues Thomas, Timothy D. Barfoot

Though the framework is general to any form of parameter learning and sensor modality, we demonstrate application to feature and uncertainty learning with a deep network for 3D lidar odometry.

Variational Inference Robotics

Variational Inference with Parameter Learning Applied to Vehicle Trajectory Estimation

no code implementations21 Mar 2020 Jeremy N. Wong, David J. Yoon, Angela P. Schoellig, Timothy D. Barfoot

Our contribution is to additionally learn parameters of our system models (which may be difficult to choose in practice) within the ESGVI framework.

Variational Inference

Mapless Online Detection of Dynamic Objects in 3D Lidar

no code implementations19 Sep 2018 David J. Yoon, Tim Y. Tang, Timothy D. Barfoot

This paper presents a model-free, setting-independent method for online detection of dynamic objects in 3D lidar data.


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