2 citations · 3 across the 4 of their papers we have counts for
8 papers · 1 filter
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…
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…
Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping
Shubhra Aich, Wenshan Wang, Parv Maheshwari +6
High-speed off-road navigation requires long-range, high-resolution maps to enable robots to safely navigate over different surfaces while avoiding dangerous obstacles. However, du…
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…
Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance
Cherie Ho, Jay Patrikar, Rogerio Bonatti +1
Safe navigation in real-time is challenging because engineers need to work with uncertain vehicle dynamics, variable external disturbances, and imperfect controllers. A common safe…
3D Human Reconstruction in the Wild with Collaborative Aerial Cameras
Cherie Ho, Andrew Jong, Harry Freeman +3
Aerial vehicles are revolutionizing applications that require capturing the 3D structure of dynamic targets in the wild, such as sports, medicine, and entertainment. The core chall…