15 citations · 15 across the 7 of their papers we have counts for
8 papers
GAPSLAM: Blending Gaussian Approximation and Particle Filters for Real-Time Non-Gaussian SLAM
Qiangqiang Huang, John J. Leonard
Inferring the posterior distribution in SLAM is critical for evaluating the uncertainty in localization and mapping, as well as supporting subsequent planning tasks aiming to reduc…
NeuSE: Neural SE(3)-Equivariant Embedding for Long-Term Object-Based Simultaneous Localization and Mapping
Jiahui Fu, Yilun Du, Kurran Singh +2
We present NeuSE, a novel Neural SE(3)-Equivariant Embedding for objects, and illustrate how it supports object-based Simultaneous Localization and Mapping (SLAM) for consistent sp…
Certifiably Correct Range-Aided SLAM
Alan Papalia, Andrew Fishberg, Brendan W. O'Neill +3
We present the first algorithm to efficiently compute certifiably optimal solutions to range-aided simultaneous localization and mapping (RA-SLAM) problems. Robotic navigation syst…
SLAM-Supported Self-Training for 6D Object Pose Estimation
Ziqi Lu, Yihao Zhang, Kevin Doherty +3
Recent progress in object pose prediction provides a promising path for robots to build object-level scene representations during navigation. However, as we deploy a robot in novel…
MAAD: A Model and Dataset for "Attended Awareness" in Driving
Deepak Gopinath, Guy Rosman, Simon Stent +4
We propose a computational model to estimate a person's attended awareness of their environment. We define attended awareness to be those parts of a potentially dynamic scene which…
Prioritized Planning for Cooperative Range-Only Localization in Multi-Robot Networks
Alan Papalia, Nicole Thumma, John Leonard
We present a novel path-planning algorithm to reduce localization error for a network of robots cooperatively localizing via inter-robot range measurements. The quality of localiza…
Network Localization Based Planning for Autonomous Underwater Vehicles with Inter-Vehicle Ranging
Alan Papalia, John Leonard
Localization between a swarm of AUVs can be entirely estimated through the use of range measurements between neighboring AUVs via a class of techniques commonly referred to as sens…
Probabilistic Data Association via Mixture Models for Robust Semantic SLAM
Kevin Doherty, David Baxter, Edward Schneeweiss +1
Modern robotic systems sense the environment geometrically, through sensors like cameras, lidar, and sonar, as well as semantically, often through visual models learned from data,…