  The pose-only (PO) visual representation has been proven to be equivalent to
the classical multiple-view geometry, while significantly improving
computational efficiency. However, its applicability for real-world navigation
in large-scale complex environments has not yet been demonstrated. In this
study, we present an efficient pose-only LiDAR-enhanced visual-inertial
navigation system (PO-VINS) to enhance the real-time performance of the state
estimator. In the visual-inertial state estimator (VISE), we propose a
pose-only visual-reprojection measurement model that only contains the inertial
measurement unit (IMU) pose and extrinsic-parameter states. We further
integrated the LiDAR-enhanced method to construct a pose-only LiDAR-depth
measurement model. Real-world experiments were conducted in large-scale complex
environments, demonstrating that the proposed PO-VISE and LiDAR-enhanced
PO-VISE reduce computational complexity by more than 50% and over 20%,
respectively. Additionally, the PO-VINS yields the same accuracy as
conventional methods. These results indicate that the pose-only solution is
efficient and applicable for real-time visual-inertial state estimation.
