33 citations · 56 across the 13 of their papers we have counts for
21 papers
Self-Supervised Feature Learning for Long-Term Metric Visual Localization
Yuxuan Chen, Timothy D. Barfoot
Visual localization is the task of estimating camera pose in a known scene, which is an essential problem in robotics and computer vision. However, long-term visual localization is…
Along Similar Lines: Local Obstacle Avoidance for Long-term Autonomous Path Following
Jordy Sehn, Yuchen Wu, Timothy D. Barfoot
Visual Teach and Repeat 3 (VT&R3), a generalization of stereo VT&R, achieves long-term autonomous path-following using topometric mapping and localization from a single rich sensor…
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…
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…