1.2k citations · 2.1k across the 52 of their papers we have counts for
12 papers · 1 filter
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim Barfoot +17
Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains. Consequently, the notion of applying learning metho…
Learning Spatiotemporal Occupancy Grid Maps for Lifelong Navigation in Dynamic Scenes
Hugues Thomas, Matthieu Gallet de Saint Aurin, Jian Zhang +1
We present a novel method for generating, predicting, and using Spatiotemporal Occupancy Grid Maps (SOGM), which embed future information of dynamic scenes. Our automated generatio…
Koopman Linearization for Data-Driven Batch State Estimation of Control-Affine Systems
Zi Cong Guo, Vassili Korotkine, James R. Forbes +1
We present the Koopman State Estimator (KoopSE), a framework for model-free batch state estimation of control-affine systems that makes no linearization assumptions, requires no pr…
Keeping an Eye on Things: Deep Learned Features for Long-Term Visual Localization
Mona Gridseth, Timothy D. Barfoot
In this paper, we learn visual features that we use to first build a map and then localize a robot driving autonomously across a full day of lighting change, including in the dark.…
Radar Odometry Combining Probabilistic Estimation and Unsupervised Feature Learning
Keenan Burnett, David J. Yoon, Angela P. Schoellig +1
This paper presents a radar odometry method that combines probabilistic trajectory estimation and deep learned features without needing groundtruth pose information. The feature ne…
Self-Calibration of the Offset Between GPS and Semantic Map Frames for Robust Localization
Wei-Kang Tseng, Angela P. Schoellig, Timothy D. Barfoot
In self-driving, standalone GPS is generally considered to have insufficient positioning accuracy to stay in lane. Instead, many turn to LIDAR localization, but this comes at the e…
Experimental Comparison of Visual and Single-Receiver GPS Odometry
Benjamin Congram, Timothy D. Barfoot
Mobile robots rely on odometry to navigate through areas where localization fails. Visual odometry (VO) is a common solution for obtaining robust and consistent relative motion est…
A Geometric Algebra Solution to Wahba's Problem
Timothy D Barfoot
We retrace Davenport's solution to Wahba's classic problem of aligning two pointclouds using the formalism of Geometric Algebra (GA). GA proves to be a natural backdrop for this pr…
Vectorial Parameterizations of Pose
Timothy D. Barfoot, James R. Forbes, Gabriele M. T. D'Eleuterio
Robotics and computer vision problems commonly require handling rigid-body motions comprising translation and rotation - together referred to as pose. In some situations, a vectori…
Unsupervised Learning of Lidar Features for Use in a Probabilistic Trajectory Estimator
David J. Yoon, Haowei Zhang, Mona Gridseth +2
We present unsupervised parameter learning in a Gaussian variational inference setting that combines classic trajectory estimation for mobile robots with deep learning for rich sen…
UAV Localization Using Autoencoded Satellite Images
Mollie Bianchi, Timothy D. Barfoot
We propose and demonstrate a fast, robust method for using satellite images to localize an Unmanned Aerial Vehicle (UAV). Previous work using satellite images has large storage and…
Relatively Lazy: Indoor-Outdoor Navigation Using Vision and GNSS
Benjamin Congram, Timothy D. Barfoot
Visual Teach and Repeat has shown relative navigation is a robust and efficient solution for autonomous vision-based path following in difficult environments. Adding additional abs…