速度重視:ドップラー速度を用いた高速・対応付け不要なLiDAR慣性オドメトリ
Need for Speed: Fast Correspondence-Free Lidar-Inertial Odometry Using Doppler Velocity
FMCW LiDARのドップラー速度とジャイロを組み合わせ、データ対応付けなしで6自由度速度を線形推定し、姿勢を積分する高速オドメトリを提案。実走行データでICP系手法と比較し、精度と計算量のトレードオフを示す。
著者: David J. Yoon, Keenan Burnett, Johann Laconte, Yi Chen, Heethesh Vhavle, Soeren Kammel, James Reuther, Timothy D. Barfoot
分類: cs.RO
原文アブストラクト
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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