6 papers
Don't Fool Me Twice: Adapting to Adversity in the Wild with Experience-Driven Reasoning
Navin Sriram Ravie, Andrew Jong, Krrish Jain +4
In robotics, dangers and adversity modes are often embodiment-specific and relative to each agent. A frontier of autonomous mobile robotics is to enable agents to operate effective…
RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models
Omar Alama, Darshil Jariwala, Avigyan Bhattacharya +3
Open-vocabulary semantic segmentation (OVSS) underpins many vision and robotics tasks that require generalizable semantic understanding. Existing approaches either rely on limited…
RAVEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation
Seungchan Kim, Omar Alama, Dmytro Kurdydyk +5
Aerial outdoor semantic navigation requires robots to explore large, unstructured environments to locate target objects. Recent advances in semantic navigation have demonstrated op…
RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration
Omar Alama, Avigyan Bhattacharya, Haoyang He +6
Open-set semantic mapping is crucial for open-world robots. Current mapping approaches either are limited by the depth range or only map beyond-range entities in constrained settin…
Aug3D: Augmenting large scale outdoor datasets for Generalizable Novel View Synthesis
Aditya Rauniyar, Omar Alama, Silong Yong +2
Recent photorealistic Novel View Synthesis (NVS) advances have increasingly gained attention. However, these approaches remain constrained to small indoor scenes. While optimizatio…
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…