10 citations · 20 across the 6 of their papers we have counts for
7 papers
TravSUITE: Traversability via Self-Supervised, Uncertainty-Aware IRL and Terrain Estimation
Samuel Triest, Amirreza Shaban, David D. Fan +2
Traversability analysis in off-road settings remains a fundamental challenge for mobile robots. Key difficulties include constructing an accurate and expressive local map from mult…
Distilling Global Traversability Priors for Image-based Affordance Prediction in Off-road Environments
Matthew Sivaprakasam, Samuel Triest, Micah Nye +5
Standard methods for autonomous navigation in unstructured terrain are prone to myopic behaviors in long-horizon scenarios. The use of metric maps built from LiDAR or cameras provi…
Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering
Muhammad Fadhil Ginting, Dong-Ki Kim, Xiangyun Meng +10
As robots become increasingly capable of operating over extended periods -- spanning days, weeks, and even months -- they are expected to accumulate knowledge of their environments…
An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments
Ali Agha, Kyohei Otsu, Benjamin Morrell +86
This paper presents an appendix to the original NeBula autonomy solution developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), participating in the DARPA Sub…
UNRealNet: Learning Uncertainty-Aware Navigation Features from High-Fidelity Scans of Real Environments
Samuel Triest, David D. Fan, Sebastian Scherer +1
Traversability estimation in rugged, unstructured environments remains a challenging problem in field robotics. Often, the need for precise, accurate traversability estimation is i…
SEEK: Semantic Reasoning for Object Goal Navigation in Real World Inspection Tasks
Muhammad Fadhil Ginting, Sung-Kyun Kim, David D. Fan +3
This paper addresses the problem of object-goal navigation in autonomous inspections in real-world environments. Object-goal navigation is crucial to enable effective inspections i…
Low Frequency Sampling in Model Predictive Path Integral Control
Bogdan Vlahov, Jason Gibson, David D. Fan +3
Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show h…