7 papers
Foresight: Iterative Reasoning About Clues that Matter for Navigation
Arthur Zhang, Carl Qi, Donne Su +3
Open-world mapless navigation from sparse language instructions requires resolving underspecified goals and inferring which environmental cues are relevant for reaching the goal. F…
GuideTWSI: A Diverse Tactile Walking Surface Indicator Dataset from Synthetic and Real-World Images for Blind and Low-Vision Navigation
Hochul Hwang, Soowan Yang, Anh N. H. Nguyen +6
Tactile Walking Surface Indicators (TWSIs) are safety-critical landmarks that blind and low-vision (BLV) pedestrians use to locate crossings and hazard zones. From our observation…
VENTURA: Adapting Image Diffusion Models for Unified Task Conditioned Navigation
Arthur Zhang, Xiangyun Meng, Luca Calliari +5
Robots must adapt to diverse human instructions and operate safely in unstructured, open-world environments. Recent Vision-Language models (VLMs) offer strong priors for grounding…
Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation
Sangmin Jung, Utkarsh Nath, Yezhou Yang +5
Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance…
CREStE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance
Arthur Zhang, Harshit Sikchi, Amy Zhang +1
We introduce CREStE, a scalable learning-based mapless navigation framework to address the open-world generalization and robustness challenges of outdoor urban navigation. Key to a…
Lift, Splat, Map: Lifting Foundation Masks for Label-Free Semantic Scene Completion
Arthur Zhang, Rainier Heijne, Joydeep Biswas
Autonomous mobile robots deployed in urban environments must be context-aware, i.e., able to distinguish between different semantic entities, and robust to occlusions. Current appr…
Looking Inside Out: Anticipating Driver Intent From Videos
Yung-chi Kung, Arthur Zhang, Junmin Wang +1
Anticipating driver intention is an important task when vehicles of mixed and varying levels of human/machine autonomy share roadways. Driver intention can be leveraged to improve…