Jeremy N. Wong — accepted AI-conference papers

2020

A Data-Driven Motion Prior for Continuous-Time Trajectory Estimation on SE(3)

Jeremy N. Wong, David J. Yoon, Angela P. Schoellig, Timothy D. Barfoot

RA-L 2020

Simultaneous trajectory estimation and mapping (STEAM) is a method for continuous-time trajectory estimation in which the trajectory is represented as a Gaussian Process (GP). Previous formulations of STEAM used a GP prior that assumed either white-noise-on-acceleration (WNOA) or white-noise-on-jerk

Cited by 31 Source ↗Scholar ↗

2020

Variational Inference With Parameter Learning Applied to Vehicle Trajectory Estimation

Jeremy N. Wong, David Juny Yoon, Angela P. Schoellig, Timothy D. Barfoot

RA-L 2020

We present parameter learning in a Gaussian variational inference setting using only noisy measurements (i.e., no groundtruth). This is demonstrated in the context of vehicle trajectory estimation, although the method we propose is general. The letter extends the Exactly Sparse Gaussian Variational

Cited by 24 Source ↗Scholar ↗