KLI-Fusion: Tightly-Coupled Kinematic-LiDAR-Inertial Odometry With Contact Foot Position Enhancement for Point-Foot Biped Robots

Accurate state estimation for point-foot biped robots is often compromised by significant $Z$ -axis drift during high-frequency, dynamic motions. This article presents KLI-fusion, a tightly coupled kinematic-LiDAR-inertial odometry framework designed to overcome this limitation. The proposed approach integrates high-frequency kinematic data, inertial measurement unit (IMU) measurements, and LiDAR point features within an iterated error-state Kalman filter (IESKF). The key innovation is an online contact foot position enhancement module, which performs real-time terrain plane fitting to generate accurate projection constraints, thereby effectively mitigating vertical estimation drift. Extensive evaluations in both simulated and challenging real-world environments demonstrate that KLI-fusion consistently outperforms state-of-the-art methods, reducing drift by 38% and achieving superior accuracy under strong impacts and vibrations.