2 citations · 3 across the 2 of their papers we have counts for
4 papers · 1 filter
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…
Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor Navigation
Hugues Thomas, Ben Agro, Mona Gridseth +2
We present a self-supervised learning approach for the semantic segmentation of lidar frames. Our method is used to train a deep point cloud segmentation architecture without any h…
DeepMEL: Compiling Visual Multi-Experience Localization into a Deep Neural Network
Mona Gridseth, Timothy D. Barfoot
Vision-based path following allows robots to autonomously repeat manually taught paths. Stereo Visual Teach and Repeat (VT\&R) accomplishes accurate and robust long-range path foll…
Building a Winning Self-Driving Car in Six Months
Keenan Burnett, Andreas Schimpe, Sepehr Samavi +5
The SAE AutoDrive Challenge is a three-year competition to develop a Level 4 autonomous vehicle by 2020. The first set of challenges were held in April of 2018 in Yuma, Arizona. Ou…