James Reuther — accepted AI-conference papers

2025

Towards Fast Correspondence-Free Odometry Using Multiple FMCW Lidars

David J. Yoon, Yi Chen, Heethesh Vhavle, James Reuther, Timothy D. Barfoot

RA-L 2025

3D FMCW lidars return relative velocity measurements via the Doppler effect, which provides a new form of information for motion estimation. In our prior work, we proposed an odometry method that avoids the conventional ICP-based approach and uses the Doppler velocity measurements in a correspondenc

Cited by 1 Source ↗Scholar ↗

2023

Need for Speed: Fast Correspondence-Free Lidar-Inertial Odometry Using Doppler Velocity

David J. Yoon, Keenan Burnett, Johann Laconte, Yi Chen, Heethesh Vhavle, Soeren Kammel +2

IROS 2023poster

In this paper, we present a fast, lightweight odometry method that uses the Doppler velocity measurements from a Frequency-Modulated Continuous-Wave (FMCW) lidar without data association. FMCW lidar is a recently emerging technology that enables per-return relative radial velocity measurements via t…

Cited by 12 Source ↗Scholar ↗