As a new disk-shaped autonomous underwater vehicle (AUV), the autonomous underwater helicopter (AUH) is devoted to subsea operations, usually diving into the seabed and docking with a subsea docking system. Due to the motion control’s performance, the AUH’s stability and steady-state accuracy are affected remarkably while docking. Moreover, considering the difficulties of hydrodynamic modeling of AUHs, the classical model-based control method is unsuitable for AUHs. Moreover, there is a large gap between the hydrodynamic simulation results and real situations. Hence, based on the data-driven principle, the linear active disturbance rejection control with a tracking differentiator (LADRC-TD) algorithm is employed for AUH depths and heading control. As the simulation experiments prove, LADRC and LADRC-TD have better anti-interference performance when compared with PID. According to the pool experiments, overshoots of the LADRC-TD are 20 cm and 3° for the depth control and heading control, respectively, which are superior to PID and LADRC. Meanwhile, the steady-state accuracy of the LADRC-TD is ±21 cm and ±2.5° for the depth and heading control, respectively, which is inferior to PID and the same as LADRC.

This letter presents the mechatronic design and implementation of a hybrid-driven disc-shaped autonomous underwater vehicle (HD-AUV). The hybrid-driven system integrates a buoyancy adjustment system and propeller thrusters, enabling the HD-AUV to achieve both high maneuverability motion and energy-efficient gliding. These capabilities correspond to two distinct motion modes: AUV mode and glider mode. In AUV mode, the HD-AUV leverages the rotational symmetry of its disc-shaped design to achieve four degree-of-freedom (4-DOF) motion control. This configuration, supported by four propeller thrusters, facilitates high-maneuverability actions, including fixed-point hovering and in-place turning. In glider mode, the integration of rotatable dorsal fins and horizontal propeller thrusters enables the HD-AUV to transition seamlessly between diving and ascending phases without the conventional mass-shifting mechanisms used in torpedo-type gliders. Numerical simulations are conducted to evaluate the steady glide performance of the HD-AUV, focusing on lift-to-drag ratios and hydrodynamic coefficients. Comprehensive pool experiments, encompassing multi-DOF maneuvers and gentle gliding, demonstrate the exceptional locomotion capabilities of the HD-AUV and validate the accuracy of the proposed dynamic model. These hybrid motion modes hold significant promise for underwater operations in complex seafloor environments.

In multi-sensor systems, time synchronization is particularly challenging for underwater integrated navigation systems incorporating acoustic positioning, where time delays can significantly degrade accuracy when measurement and fusion epochs are misaligned. This paper introduces a tightly coupled navigation framework that integrates a passive inverted ultra-short baseline (piUSBL) acoustic positioning system, a strapdown inertial navigation system (SINS), and a depth gauge under precise time synchronization. The framework fuses piUSBL azimuth and slant range with depth measurements, avoiding poor vertical-angle observability in planar arrays. By combining synchronized timing with acoustic signal processing, the proposed method transforms delay from an unobservable error into a measurable parameter, enabling explicit quantification of both acoustic propagation and system processing delays. Field experiments demonstrate that the proposed approach reduces position RMSE by 44.02% and maximum error by 40.79% compared to the uncompensated baseline, while achieving further RMSE reductions of 37.66% and 35.82% in horizontal directions relative to filter-based delay compensation. The results confirm that explicit delay measurement outperforms filter-based estimation, though instantaneous performance remains sensitive to acoustic signal quality, emphasizing the need for robust signal processing alongside accurate time synchronization in latency-sensitive multi-sensor systems.