7 citations · 16 across the 22 of their papers we have counts for
22 papers
Exploiting Chordal Sparsity for Globally Optimal Estimation with Factor Graphs
Avinash Subramanian, Connor Holmes, Timothy D. Barfoot +2
Robust and efficient state estimation is crucial for perception, navigation, and control in robotics. State estimation problems are conveniently modeled using the factor-graph fram…
Smoothing Out the Edges: Continuous-Time Estimation with Gaussian Process Motion Priors on Factor Graphs
Connor Holmes, Sven Lilge, Zi Cong Guo +2
Continuous-time state estimation is gaining in popularity due to its abilities to provide smooth solutions, handle asynchronous sensors, and interpolate between data points. While…
Dr-PoGO: Direct Radar Pose-Graph Optimization
Cedric Le Gentil, Weican Li, Leonardo Brizi +1
This paper introduces Dr-PoGO, a method for Simultaneous Localization And Mapping (SLAM) using a 2D spinning radar. Unlike cameras or lidars that require line-of-sight, millimetre-…
Degeneracy-Resilient Teach and Repeat for Geometrically Challenging Environments Using FMCW Lidar
Katya M. Papais, Wenda Zhao, Timothy D. Barfoot
Teach and Repeat (T&R) topometric navigation enables robots to autonomously repeat previously traversed paths without relying on GPS, making it well suited for operations in GPS-de…
Continuum Robot Localization using Distributed Time-of-Flight Sensors
Spencer Teetaert, Giammarco Caroleo, Marco Pontin +4
Localization and mapping of an environment are crucial tasks for any robot operating in unstructured environments. Time-of-flight (ToF) sensors (e.g.,~lidar) have proven useful in…
Lunar Rover Cargo Transport: Mission Concept and Field Test
Alexander Krawciw, Nicolas Olmedo, Faizan Rehmatullah +3
In future operations on the lunar surface, automated vehicles will be required to transport cargo between known locations. Such vehicles must be able to navigate precisely in safe…
Ratatouille: Imitation Learning Ingredients for Real-world Social Robot Navigation
James R. Han, Mithun Vanniasinghe, Hshmat Sahak +2
Scaling Reinforcement Learning to in-the-wild social robot navigation is both data-intensive and unsafe, since policies must learn through direct interaction and inevitably encount…
Sound Source Localization for Human-Robot Interaction in Outdoor Environments
Victor Liu, Timothy Du, Jordy Sehn +2
This paper presents a sound source localization strategy that relies on a microphone array embedded in an unmanned ground vehicle and an asynchronous close-talking microphone near…
Toward Teach and Repeat Across Seasonal Deep Snow Accumulation
Matěj Boxan, Alexander Krawciw, Timothy D. Barfoot +1
Teach and repeat is a rapid way to achieve autonomy in challenging terrain and off-road environments. A human operator pilots the vehicles to create a network of paths that are map…
Tunable Virtual IMU Frame by Weighted Averaging of Multiple Non-Collocated IMUs
Yizhou Gao, Tim Barfoot
We present a new method to combine several rigidly connected but physically separated IMUs through a weighted average into a single virtual IMU (VIMU). This has the benefits of (i)…
RaSCL: Radar to Satellite Crossview Localization
Blerim Abdullai, Tony Wang, Xinyuan Qiao +2
GNSS is unreliable, inaccurate, and insufficient in many real-time autonomous field applications. In this work, we present a GNSS-free global localization solution that contains a…
Balancing Act: Trading Off Odometry and Map Registration for Efficient Lidar Localization
Katya M. Papais, Daniil Lisus, Cedric Le Gentil +2
Most autonomous vehicles rely on accurate and efficient localization, which is achieved by comparing live sensor data to a preexisting map, to navigate their environment. Balancing…
Radar Teach and Repeat: Architecture and Initial Field Testing
Xinyuan Qiao, Alexander Krawciw, Sven Lilge +1
Frequency-modulated continuous-wave (FMCW) scanning radar has emerged as an alternative to spinning LiDAR for state estimation on mobile robots. Radar's longer wavelength is less a…
The Finer Points: A Systematic Comparison of Point-Cloud Extractors for Radar Odometry
Elliot Preston-Krebs, Daniil Lisus, Timothy D. Barfoot
A key element of many odometry pipelines using spinning frequency-modulated continuous-wave (FMCW) radar is the extraction of a point-cloud from the raw signal. This extraction gre…
Marginalizing and Conditioning Gaussians onto Linear Approximations of Smooth Manifolds with Applications in Robotics
Zi Cong Guo, James R. Forbes, Timothy D. Barfoot
We present closed-form expressions for marginalizing and conditioning Gaussians onto linear manifolds, and demonstrate how to apply these expressions to smooth nonlinear manifolds…
Exploiting Chordal Sparsity for Fast Global Optimality with Application to Localization
Frederike Dümbgen, Connor Holmes, Timothy D. Barfoot
In recent years, many estimation problems in robotics have been shown to be solvable to global optimality using their semidefinite relaxations. However, the runtime complexity of o…
FoMo: A Proposal for a Multi-Season Dataset for Robot Navigation in Forêt Montmorency
Matěj Boxan, Alexander Krawciw, Effie Daum +4
In this paper, we propose the FoMo (Forêt Montmorency) dataset: a comprehensive, multi-season data collection. Located in the Montmorency Forest, Quebec, Canada, our dataset will c…
IMU as an Input vs. a Measurement of the State in Inertial-Aided State Estimation
Keenan Burnett, Angela P. Schoellig, Timothy D. Barfoot
Treating IMU measurements as inputs to a motion model and then preintegrating these measurements has almost become a de-facto standard in many robotics applications. However, this…
LaserSAM: Zero-Shot Change Detection Using Visual Segmentation of Spinning LiDAR
Alexander Krawciw, Sven Lilge, Timothy D. Barfoot
This paper presents an approach for applying camera perception techniques to spinning LiDAR data. To improve the robustness of long-term change detection from a 3D LiDAR, range and…
Continuous-time Trajectory Estimation: A Comparative Study Between Gaussian Process and Spline-based Approaches
Jacob Johnson, Joshua Mangelson, Timothy Barfoot +1
Continuous-time trajectory estimation is an attractive alternative to discrete-time batch estimation due to the ability to incorporate high-frequency measurements from asynchronous…
Change of Scenery: Unsupervised LiDAR Change Detection for Mobile Robots
Alexander Krawciw, Jordy Sehn, Timothy D. Barfoot
This paper presents a fully unsupervised deep change detection approach for mobile robots with 3D LiDAR. In unstructured environments, it is infeasible to define a closed set of se…
Multivariate Gaussian Variational Inference by Natural Gradient Descent
Timothy D. Barfoot
This short note reviews so-called Natural Gradient Descent (NGD) for multivariate Gaussians. The Fisher Information Matrix (FIM) is derived for several different parameterizations…