4 papers
MapEx: Indoor Structure Exploration with Probabilistic Information Gain from Global Map Predictions
Cherie Ho, Seungchan Kim, Brady Moon +6
Exploration is a critical challenge in robotics, centered on understanding unknown environments. In this work, we focus on robots exploring structured indoor environments which are…
SALON: Self-supervised Adaptive Learning for Off-road Navigation
Matthew Sivaprakasam, Samuel Triest, Cherie Ho +5
Autonomous robot navigation in off-road environments presents a number of challenges due to its lack of structure, making it difficult to handcraft robust heuristics for diverse sc…
Map It Anywhere (MIA): Empowering Bird's Eye View Mapping using Large-scale Public Data
Cherie Ho, Jiaye Zou, Omar Alama +7
Top-down Bird's Eye View (BEV) maps are a popular representation for ground robot navigation due to their richness and flexibility for downstream tasks. While recent methods have s…
Learning-on-the-Drive: Self-supervised Adaptation of Visual Offroad Traversability Models
Eric Chen, Cherie Ho, Mukhtar Maulimov +2
Autonomous offroad driving is essential for applications like emergency rescue, military operations, and agriculture. Despite progress, systems struggle with high-speed vehicles ex…