3 accepted papers
This paper presents a new tightly coupled LiDAR-inertial odometry (LIO) scheme for a quadruped robot operating under fluctuating conditions. By proposing external disturbance modeling, the profile of unknown disturbances and noise on the IMU is effectively characterized using the time delay estimati
This work presents a tightly coupled LiDAR–inertial odometry (LIO) framework tailored for quadruped robots operating under vibration and fluctuating conditions. By integrating time delay estimation (TDE) into an error-state Kalman filter (ESKF), external disturbances affecting the IMU are explicitly…
This letter presents a new tightly coupled LiDAR-visual-inertial odometry scheme for agricultural autonomous machinery under a structureless environment and the presence of fluctuation uncertainties. By proposing the robust adaptive filter, the effects of unknown disturbances and noises are signific