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Parker Ewen

8 accepted papers

2026

SLIM-VDB: A Real-Time 3D Probabilistic Semantic Mapping Framework

RA-L 2026

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 from the computer graphics community, such as OpenVDB, have demonstrated significantly improved computational and memory e

Cited by 0SourcecodeScholar
2026

SLIM-VDB: A Real-Time 3D Probabilistic Semantic Mapping Framework

ICRA 2026poster

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 from the computer graphics community, such as OpenVDB, have demonstrated significantly improved computational and memory e…

2026

These Magic Moments: Differentiable Uncertainty Quantification of Radiance Field Models

ICRA 2026poster

Uncertainty quantification is crucial for autonomous systems, enabling safe and robust decision making in tasks ranging from active perception to robotic planning. This paper introduces a novel approach to quantify uncertainty for radiance fields by deriving pixel-wise moment expressions from the re…

2025

LatentBKI: Open-Dictionary Continuous Mapping in Visual-Language Latent Spaces With Quantifiable Uncertainty

RA-L 2025

This letter introduces a novel probabilistic mapping algorithm, LatentBKI, which enables open-vocabulary mapping with quantifiable uncertainty. Traditionally, semantic mapping algorithms focus on a fixed set of semantic categories which limits their applicability for complex robotic tasks. Vision-La

Cited by 4SourcecodeScholar
2025

Modeling Uncertainty in 3D Gaussian Splatting Through Continuous Semantic Splatting

ICRA 2025

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 introduced algorithms which learn to rasterize features in 3D-GS for enhanced scene understanding, 3D-GS can fail without warn

Cited by 14SourceScholar
2024

You’ve Got to Feel It To Believe It: Multi-Modal Bayesian Inference for Semantic and Property Prediction

RSS 2024poster

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 such as friction or weight. Estimating such properties using learning is challenging due to the large amounts of labelled…

2022

These Maps are Made for Walking: Real-Time Terrain Property Estimation for Mobile Robots

RA-L 2022

The equations of motion governing mobile robots are dependent on terrain properties such as the coefficient of friction, and contact model parameters. Estimating these properties is thus essential for robotic navigation. Ideally any map estimating terrain properties should run in real time, mitigate

Cited by 30SourcecodeScholar
2021

Generating Continuous Motion and Force Plans in Real-Time for Legged Mobile Manipulation

ICRA 2021poster

Manipulators can be added to legged robots, allowing them to interact with and change their environment. Legged mobile manipulation planners must consider how contact forces generated by these manipulators affect the system. Current planning strategies either treat these forces as immutable during p…

Cited by 24SourceScholar