  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.
