Autonomous underwater vehicles (AUVs) have become an important technology in the field of the Internet of Underwater Things (IoUT). However, the complexity and unknown nature of the underwater environment poses a great challenge to the autonomous operation of AUVs. An efficient and stable path-planning algorithm is the key for AUVs to achieve autonomous operation. To address the above problems, this article proposes an improved exponential distribution optimizer (IEDO) for 3-D path planning. In the proposed algorithm, population initialization, the optimization algorithm itself, and the local optimum problem are all addressed and improved. The algorithm population is first initialized using an oriented initialization method that obeys a Gaussian distribution to improve the efficiency of the algorithm in the early stages. Second, for the IEDO algorithm itself, the convergence rate of the algorithm is further improved by adding the guided solution generated by its iterative process to the iterative selection of the population. Finally, the crossover-mutation idea of the genetic algorithm is integrated to improve the global search ability of the population and avoid falling into the local optimum problem. In terms of algorithm validation, two real seabed terrain data sets are used for a simulation verification of the algorithm and compared with the existing algorithms. The results prove that the IEDO algorithm proposed in this article has a strong convergence speed, strong global search capability, and good path qualities.

Underwater gliders are prevailing in oceanic observation nowadays for their flexible deployment and low cost. However, the limited onboard energy constrains their application, hence the motion pattern optimization and energy analysis are the key to maximizing the range of the glider while maintaining the acceptable navigation preciseness of the glider. In this work, a Multi-Objective Artificial Bee Colony (MOABC) algorithm is used to solve the constrained hybrid non-convex multi-objective optimization problem about range and accuracy of gliders in combination with specific glider dynamics models. The motion parameters Pareto front that balances the navigational index referring to range and preciseness are obtained, relevant gliding profile motion results are simulated simultaneously, and the results are compared with the conventional gliding patterns to examine the quality of the solution. Comparison shows that, with the utilization of the algorithm, glider voyage performance with respect to endurance and preciseness can be effectively improved.

The use of a multi-functional autonomous underwater vehicle (AUV) as a platform for making turbulence measurements in the ocean is developed. The layout optimization of the turbulence package and platform motion performance are limitation problems in turbulent AUV design. In this study, the computational fluid dynamics (CFD) method has been used to determine the optimized layout position and distance of the shear probe integrated into an AUV. When placed 0.8 D ahead of the AUV nose along the axis, the shear probe is not influenced by flow distortion and can contact the water body first. To analyze the motion of the turbulence AUV, the dynamic model of turbulence AUV for planar flight is obtained. Then, the mathematical equations of speed and angle of attack under steady-state motion have also been obtained. By calculating the hydrodynamic coefficients of the turbulence AUV and given system parameters, the simulation analysis has been conducted. The simulation results demonstrated that the speed of turbulent AUV is 0.5–1 m/s, and the maximum angle of attack is less than 6.5°, which meets the observation requirements of the shear probe. In addition, turbulence AUV conducted a series of sea-trials in the northern South China Sea to illustrate the validity of the design and measurement. Two continuous profiles (1000 m) with a horizontal distance of 10 km were completed, and numerous high-quality spatiotemporal turbulence data were obtained. These profiles demonstrate the superior flight performance of turbulence AUV. Analysis shows that the measured data are of high quality, with the shear spectra being in very good agreement with the Nasmyth spectrum. Dissipation rates are consistent with background shear. When shear velocity is weak, the measurement of dissipation rate is 10⁻¹⁰ W Kg⁻¹. All indications are that the turbulence AUV is suitable for long-term, contiguous ocean microstructure measurements, which will provide data needed to understand the temporal and spatial variability of the turbulent processes in the oceans.

This study developed a new cross-platform instrument for microstructure turbulence measurement (CPMTM) and evaluated its performance. The CPMTM is designed as an “all-in-one” payload that can be easily integrated with a variety of marine instrumentation platforms. The sensors in the CPMTM include two shear probes, a fast-response temperature probe, and an accelerometer for monitoring vibrations. In addition, a custom-designed flexible connection vibration-damping device is used to isolate platform vibrations. To validate the CPMTM performance, a direct comparison was carried out with a reference acoustic Doppler velocimeter in a controlled flume for four background turbulence levels. The results of the comparison show that the velocity spectra measured by the CPMTM and ADV w components are in agreement, which demonstrates the ability of the CPMTM to acquire accurate turbulence data. Furthermore, the CPMTM was integrated into the long-range Sea-Whale 2000 AUV and tested in the northern South China Sea in September 2020. The data collected by the CPMTM show that the measured shear spectrum of the noise reduction agrees well with the empirical Nasmyth spectrum. Turbulent kinetic energy dissipation rates as low as 7 × 10⁻¹⁰ W kg⁻¹ can be resolved. Laboratory and field experiments illustrate that the CPMTM has an extraordinarily low noise level and is validated for turbulence measurements.

Autonomous underwater vehicle (AUV) has important significance for understanding, researching and developing the ocean. The research of path planning plays an important role in the safety of AUV and the improvement of work efficiency. Aiming at the complex underwater environment, irregular obstacles and planning difficulties, this paper proposes a dimension reduction path planning method suitable for three-dimensional space path planning. The space is expressed by the combination of horizontal stratification and longitudinal cutting, which simplifies the environmental model and improves the dimensionality disaster of path planning and long planning time. Furthermore, the inverse pruning and node reconstruction methods are used to further optimize the shortening path, which improves the practical value of the path. And the algorithm is fast, which reduces the energy consumption during the AUV travel. The simulation results show that the design path planning method is simple and effective, and it is suitable for complex underwater environment.

Turbulent energy cascade and intermittency are very important characteristics in the turbulent energy evolution process. However, understanding the temporal–spatial features of kinetic energy transfer and quantifying the correlations between different scales of turbulent energy remains an outstanding challenge. To deeply understand the spatial–temporal features in the energy transfer process, an integrated features identification and extraction method is proposed to quantitatively investigate the correlations using the ocean shear turbulence measured by an autonomous vertical reciprocating profiler (AVRP). The proposed integrated method mainly contains two parallel features analysis modules: first, temporal multiscale features structures of the nonlinear and nonstationary turbulent cascade are identified by Variational Mode Decomposition (VMD); then, the ocean microstructure shear fluctuation data are decomposed into a series of intrinsic mode functions (IMFs), which are characterized by different time scales and frequency bandwidths. The local features of energy transfer are identified when the local intermittency peaks overlap and the phase-synchronization case occurs between two neighboring scales; second, the spatial statistical characteristics of the turbulent energy dissipation are quantitatively studied. The cumulative probability distribution functions (CPDFs) of kinetic energy dissipation are approximated well by a normal distribution, indicating that the turbulent dissipation process exhibits a robust spatial scaling correlation and a few intense dissipation locations dominate the integrated process. Finally, the proposed integrated method is evaluated through experiments using an autonomous vertical reciprocating profiler deployed in the South China Sea. Preliminary experimental results show that the proposed novel method is useful to improve our understanding of turbulent energy transfer and the evolution process in the ocean dynamic systems.