5 papers · 1 filter
SLIM-VDB: A Real-Time 3D Probabilistic Semantic Mapping Framework
Anja Sheppard, Parker Ewen, Joey Wilson +6
This paper introduces SLIM-VDB, a new lightweight semantic mapping system with probabilistic semantic fusion for closed-set or open-set dictionaries. Advances in data structures fr…
Let's Make a Splan: Risk-Aware Trajectory Optimization in a Normalized Gaussian Splat
Jonathan Michaux, Seth Isaacson, Challen Enninful Adu +6
Neural Radiance Fields and Gaussian Splatting have recently transformed computer vision by enabling photo-realistic representations of complex scenes. However, they have seen limit…
Modeling Uncertainty in 3D Gaussian Splatting through Continuous Semantic Splatting
Joey Wilson, Marcelino Almeida, Min Sun +6
In this paper, we present a novel algorithm for probabilistically updating and rasterizing semantic maps within 3D Gaussian Splatting (3D-GS). Although previous methods have introd…
ConvBKI: Real-Time Probabilistic Semantic Mapping Network with Quantifiable Uncertainty
Joey Wilson, Yuewei Fu, Joshua Friesen +5
In this paper, we develop a modular neural network for real-time {\color{black}(> 10 Hz)} semantic mapping in uncertain environments, which explicitly updates per-voxel probabilist…
You've Got to Feel It To Believe It: Multi-Modal Bayesian Inference for Semantic and Property Prediction
Parker Ewen, Hao Chen, Yuzhen Chen +4
Robots must be able to understand their surroundings to perform complex tasks in challenging environments and many of these complex tasks require estimates of physical properties s…