Samuel Triest

According to our database, Samuel Triest authored at least 12 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

SALON: Self-supervised Adaptive Learning for Off-road Navigation.

Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Shubhra Aich, Jeric Lew, Isaiah Adu, Wenshan Wang, Sebastian A. Scherer

Proceedings of the IEEE International Conference on Robotics and Automation, 2025

2024

Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping.

Shubhra Aich, Wenshan Wang, Parv Maheshwari, Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Jason M. Gregory, John G. Rogers III, Sebastian A. Scherer

CoRR, 2024

UNRealNet: Learning Uncertainty-Aware Navigation Features from High-Fidelity Scans of Real Environments.

Samuel Triest, David D. Fan, Sebastian A. Scherer, Ali-Akbar Agha-Mohammadi

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

TartanDrive 2.0: More Modalities and Better Infrastructure to Further Self-Supervised Learning Research in Off-Road Driving Tasks.

Matthew Sivaprakasam, Parv Maheshwari, Mateo Guaman Castro, Samuel Triest, Micah Nye, Steven Willits, Andrew Saba, Wenshan Wang, Sebastian A. Scherer

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Velociraptor: Leveraging Visual Foundation Models for Label-Free, Risk-Aware Off-Road Navigation.

Samuel Triest, Matthew Sivaprakasam, Shubhra Aich, David D. Fan, Wenshan Wang, Sebastian A. Scherer

Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

2023

PIAug - Physics Informed Augmentation for Learning Vehicle Dynamics for Off-Road Navigation.

Parv Maheshwari, Wenshan Wang, Samuel Triest, Matthew Sivaprakasam, Shubhra Aich, John G. Rogers III, Jason M. Gregory, Sebastian A. Scherer

CoRR, 2023

Learning Risk-Aware Costmaps via Inverse Reinforcement Learning for Off-Road Navigation.

Samuel Triest, Mateo Guaman Castro, Parv Maheshwari, Matthew Sivaprakasam, Wenshan Wang, Sebastian A. Scherer

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

How Does It Feel? Self-Supervised Costmap Learning for Off-Road Vehicle Traversability.

Mateo Guaman Castro, Samuel Triest, Wenshan Wang, Jason M. Gregory, Felix A. Sanchez, John G. Rogers, Sebastian A. Scherer

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

2022

TartanDrive: A Large-Scale Dataset for Learning Off-Road Dynamics Models.

Samuel Triest, Matthew Sivaprakasam, Sean J. Wang, Wenshan Wang, Aaron M. Johnson, Sebastian A. Scherer

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

Improving Off-road Planning Techniques with Learned Costs from Physical Interactions.

Matthew Sivaprakasam, Samuel Triest, Wenshan Wang, Peng Yin, Sebastian A. Scherer

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Rough Terrain Navigation Using Divergence Constrained Model-Based Reinforcement Learning.

Sean J. Wang, Samuel Triest, Wenshan Wang, Sebastian A. Scherer, Aaron M. Johnson

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Learning Highway Ramp Merging Via Reinforcement Learning with Temporally-Extended Actions.

Samuel Triest, Adam Villaflor, John M. Dolan

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020