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arXiv · 2303.06511

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·James Reuther·Timothy D. Barfoot
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Abstract

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 the Doppler effect. Since the Doppler measurement model is linear with respect to the 6-degrees-of-freedom (DOF) vehicle velocity, we can formulate a linear continuous-time estimation problem for the velocity and numerically integrate for the 6-DOF pose estimate afterward. The caveat is that angular velocity is not observable with a single FMCW lidar. We address this limitation by also incorporating the angular velocity measurements from a gyroscope. This results in an extremely efficient odometry method that processes lidar frames at an average wall-clock time of 5.64ms on a single thread, well below the 10Hz operating rate of the lidar we tested. We show experimental results on real-world driving sequences and compare against state-of-the-art Iterative Closest Point (ICP)-based odometry methods, presenting a compelling trade-off between accuracy and computation. We also present an algebraic observability study, where we demonstrate in theory that the Doppler measurements from multiple FMCW lidars are capable of observing all 6 degrees of freedom (translational and angular velocity).

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David J. Yoon, Keenan Burnett, Johann Laconte, Yi Chen, Heethesh Vhavle, Soeren Kammel, James Reuther, Timothy D. Barfoot. 2023-03-11. Need for Speed: Fast Correspondence-Free Lidar-Inertial Odometry Using Doppler Velocity. https://arxiv.org/abs/2303.06511

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