activity
20182021
most citedRadar Odometry Combining Probabilistic Estimation and Unsupervised Feature Learning

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO20212 cited

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…

cs.RO2020

Do We Need to Compensate for Motion Distortion and Doppler Effects in Spinning Radar Navigation?

Keenan Burnett, Angela P. Schoellig, Timothy D. Barfoot

In order to tackle the challenge of unfavorable weather conditions such as rain and snow, radar is being revisited as a parallel sensing modality to vision and lidar. Recent works…

cs.RO2020

Zeus: A System Description of the Two-Time Winner of the Collegiate SAE AutoDrive Competition

Keenan Burnett, Jingxing Qian, Xintong Du +14

The SAE AutoDrive Challenge is a three-year collegiate competition to develop a self-driving car by 2020. The second year of the competition was held in June 2019 at MCity, a mock…

cs.RO2019

aUToTrack: A Lightweight Object Detection and Tracking System for the SAE AutoDrive Challenge

Keenan Burnett, Sepehr Samavi, Steven L. Waslander +2

The University of Toronto is one of eight teams competing in the SAE AutoDrive Challenge -- a competition to develop a self-driving car by 2020. After placing first at the Year 1 c…

cs.RO2018

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…