activity
20212026
most citedConvolutional Bayesian Kernel Inference for 3D Semantic Mapping

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

HyperSpace: A Generalized Framework for Spatial Encoding in Hyperdimensional Representations

Shay Snyder, Andrew Capodieci, David Gorsich +1

Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We introduce HyperSpace, an open-sourc…

cs.AI2026

SRMU: Relevance-Gated Updates for Streaming Hyperdimensional Memories

Shay Snyder, Andrew Capodieci, David Gorsich +1

Sequential associative memories (SAMs) are difficult to build and maintain in real-world streaming environments, where observations arrive incrementally over time, have imbalanced…

cs.RO2025

Generalizable Reinforcement Learning with Biologically Inspired Hyperdimensional Occupancy Grid Maps for Exploration and Goal-Directed Path Planning

Shay Snyder, Ryan Shea, Andrew Capodieci +2

Real-time autonomous systems utilize multi-layer computational frameworks to perform critical tasks such as perception, goal finding, and path planning. Traditional methods impleme…

cs.RO2024

Brain Inspired Probabilistic Occupancy Grid Mapping with Vector Symbolic Architectures

Shay Snyder, Andrew Capodieci, David Gorsich +1

Real-time robotic systems require advanced perception, computation, and action capability. However, the main bottleneck in current autonomous systems is the trade-off between compu…

cs.RO2023

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…

cs.RO2022★ 1 cited

Convolutional Bayesian Kernel Inference for 3D Semantic Mapping

Joey Wilson, Yuewei Fu, Arthur Zhang +5

Robotic perception is currently at a cross-roads between modern methods, which operate in an efficient latent space, and classical methods, which are mathematically founded and pro…

cs.CV2022

MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environments

Joey Wilson, Jingyu Song, Yuewei Fu +5

This work addresses a gap in semantic scene completion (SSC) data by creating a novel outdoor data set with accurate and complete dynamic scenes. Our data set is formed from random…

cs.RO2021

Dynamic Semantic Occupancy Mapping using 3D Scene Flow and Closed-Form Bayesian Inference

Aishwarya Unnikrishnan, Joey Wilson, Lu Gan +4

This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. Existence of dynamic objects in…