David J. Yoon

Orcid: 0000-0002-4838-7422

Affiliations:

University of Toronto, Canada

According to our database¹, David J. Yoon authored at least 22 papers between 2017 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2025

Are Doppler Velocity Measurements Useful for Spinning Radar Odometry?

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., January, 2025

2024

Are Doppler Velocity Measurements Useful for Spinning Radar Odometry?

[BibT_eX]

[DOI]

CoRR, 2024

2023

Boreas: A multi-season autonomous driving dataset.

[BibT_eX]

[DOI]

Int. J. Robotics Res., January, 2023

Picking up Speed: Continuous-Time Lidar-Only Odometry Using Doppler Velocity Measurements.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2023

Need for Speed: Fast Correspondence-Free Lidar Odometry Using Doppler Velocity.

[BibT_eX]

[DOI]

CoRR, 2023

Need for Speed: Fast Correspondence-Free Lidar-Inertial Odometry Using Doppler Velocity.

[BibT_eX]

[DOI]

IROS, 2023

Towards Consistent Batch State Estimation Using a Time-Correlated Measurement Noise Model.

[BibT_eX]

[DOI]

David J. Yoon

Timothy D. Barfoot

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2022

Should Radar Replace Lidar in All-Weather Mapping and Localization?

[BibT_eX]

[DOI]

CoRR, 2022

Boreas: A Multi-Season Autonomous Driving Dataset.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Unsupervised Learning of Lidar Features for Use ina Probabilistic Trajectory Estimator.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

Zeus: A system description of the two-time winner of the collegiate SAE autodrive competition.

[BibT_eX]

[DOI]

Arkady Arkhangorodsky

J. Field Robotics, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Radar Odometry Combining Probabilistic Estimation and Unsupervised Feature Learning.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

2020

Variational Inference With Parameter Learning Applied to Vehicle Trajectory Estimation.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2020

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

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2020

Exactly sparse Gaussian variational inference with application to derivative-free batch nonlinear state estimation.

[BibT_eX]

[DOI]

Timothy D. Barfoot

James Richard Forbes

David J. Yoon

Int. J. Robotics Res., 2020

2019

A White-Noise-on-Jerk Motion Prior for Continuous-Time Trajectory Estimation on SE(3).

[BibT_eX]

[DOI]

Tim Yuqing Tang

David Juny Yoon

Timothy D. Barfoot

IEEE Robotics Autom. Lett., 2019

Mapless Online Detection of Dynamic Objects in 3D Lidar.

[BibT_eX]

[DOI]

David J. Yoon

Tim Y. Tang

Timothy D. Barfoot

Proceedings of the 16th Conference on Computer and Robot Vision, 2019

2018

Developing and deploying a tethered robot to map extremely steep terrain.

[BibT_eX]

[DOI]

J. Field Robotics, 2018

Learning a Bias Correction for Lidar-Only Motion Estimation.

[BibT_eX]

[DOI]

Proceedings of the 15th Conference on Computer and Robot Vision, 2018

2017

Field Deployment of the Tethered Robotic eXplorer to Map Extremely Steep Terrain.

[BibT_eX]

[DOI]

Proceedings of the Field and Service Robotics, 2017

David J. Yoon

Timeline

Legend:

Links

Online presence:

On csauthors.net:

Bibliography

Loading...