  Using different sensors in an autonomous vehicle (AV) can provide multiple
constraints to optimize AV location estimation. In this paper, we present a
low-cost GPS-assisted LiDAR state estimation system for AVs. Firstly, we
utilize LiDAR to obtain highly precise 3D geometry data. Next, we use an
inertial measurement unit (IMU) to correct point cloud misalignment caused by
incorrect place recognition. The estimated LiDAR odometry and IMU measurement
are then jointly optimized. We use a lost-cost GPS instead of a real-time
kinematic (RTK) module to refine the estimated LiDAR-inertial odometry. Our
low-cost GPS and LiDAR complement each other, and can provide highly accurate
vehicle location information. Moreover, a low-cost GPS is much cheaper than an
RTK module, which reduces the overall AV sensor cost. Our experimental results
demonstrate that our proposed GPS-aided LiDAR-inertial odometry system performs
very accurately. The accuracy achieved when processing a dataset collected in
an industrial zone is approximately 0.14 m.
