ROAMER: レーダー速度統合によるマルチモーダル状態推定を用いた堅牢なオフロード自律走行
ROAMER: Robust Offroad Autonomy using Multimodal State Estimation with Radar Velocity Integration
FMCWレーダーの前方速度計測をLiDAR慣性オドメトリのグラフベーススムーザに統合し、LiDARデータが劣化・欠損しても高速オフロード環境で安定した状態推定を実現した。
著者: Morten Nissov, Shehryar Khattak, Jeffrey A. Edlund, Curtis Padgett, Kostas Alexis, Patrick Spieler
分類: cs.RO
原文アブストラクト
Reliable offroad autonomy requires low-latency, high-accuracy state estimates of pose as well as velocity, which remain viable throughout environments with sub-optimal operating conditions for the utilized perception modalities. As state estimation remains a single point of failure system in the majority of aspiring autonomous systems, failing to address the environmental degradation the perception sensors could potentially experience given the operating conditions, can be a mission-critical shortcoming. In this work, a method for integration of radar velocity information in a LiDAR-inertial odometry solution is proposed, enabling consistent estimation performance even with degraded LiDAR-inertial odometry. The proposed method utilizes the direct velocity-measuring capabilities of an Frequency Modulated Continuous Wave (FMCW) radar sensor to enhance the LiDAR-inertial smoother solution onboard the vehicle through integration of the forward velocity measurement into the graph-based smoother. This leads to increased robustness in the overall estimation solution, even in the absence of LiDAR data. This method was validated by hardware experiments conducted onboard an all-terrain vehicle traveling at high speed, ~12 m/s, in demanding offroad environments.
