Dhruv Ahuja — accepted AI-conference papers

2026

Uncertainty-driven 3D Gaussian Splatting Active Mapping via Anisotropic Visibility Field

Shangjie Xue, Jesse Dill, Dhruv Ahuja, Frank Dellaert, Panagiotis Tsiotras, Danfei Xu

CVPR 2026

We present Gaussian Splatting Anisotropic Visibility Field (GAVIS), a novel framework for uncertainty quantification and active mapping in 3DGS. Our key insight is that regions unseen from the training views yield unreliable predictions from the 3DGS. To address this, we introduce a principled and e

Cited by 0 Source ↗code ↗Scholar ↗

2025

Dynamic Gap: Safe Gap-based Navigation in Dynamic Environments

Max Asselmeier, Dhruv Ahuja, Abdel Zaro, Ahmad Abuaish, Ye Zhao, Patricio A. Vela

ICRA 2025

This paper extends the family of gap-based local planners to unknown dynamic environments through generating provably collision-free properties for hierarchical navigation systems. Existing perception-informed local planners that operate in dynamic environments rely on emergent or empirical robustne

Cited by 2 Source ↗code ↗Scholar ↗