In this paper, we propose a modified hybrid Salp Swarm Algorithm (SSA) and Aquila Optimizer (AO) named IHSSAO for UAV path planning in complex terrain. The primary logic of the proposed IHSSAO is to enhance the performance of AO by introducing the leader mechanism of SSA, tent chaotic map, and pinhole imaging opposition-based learning strategy. Firstly, the tent chaotic map is utilized to substitute the randomly generated initial population in the original algorithm to increase the diversity of the initial individuals. Secondly, we integrate the leader mechanism of SSA into the position update formulation of the basic AO, which enables the search individuals to fully utilize the optimal solution information and enhances the global search capability of AO. Thirdly, we introduce the pinhole imaging opposition-based learning in the proposed IHSSAO to enhance the capability to escape from the local optimization. To verify the effectiveness of the proposed IHSSAO algorithm, we tested it against SSA, AO, and five other advanced meta-heuristic algorithms on 23 classical benchmark functions and 17 IEEE CEC2017 test functions. The experimental results indicate that the proposed IHSSAO is superior to the other seven algorithms in most cases. Eventually, we applied the IHSSAO, SSA, and AO to solve the UAV path planning problem. The experimental results verify that the IHSSAO is superior to the basic SSA and AO for solving the UAV path planning problem in complex terrain.

In this paper, we examine potential methods for autonomously tracking and landing multi-rotor unmanned aerial vehicles (UAVs), a complex yet essential problem. Autonomous tracking and landing control technology utilizes visual navigation, relying solely on vision and landmarks to track targets and achieve autonomous landing. This technology improves the UAV’s environment perception and autonomous flight capabilities in GPS-free scenarios. In particular, we are researching tracking and landing as a cohesive unit, devising a switching plan for various UAV tracking and landing modes, and creating a flight controller that has an inner and outer loop structure based on relative position estimation. The inner and outer nested markers aid in the autonomous tracking and landing of UAVs. Optimal parameters are determined via optimized experiments on the measurements of the inner and outer markers. An indoor experimental platform for tracking and landing UAVs was established. Tracking performance was verified by tracking three trajectories of an unmanned ground vehicle (UGV) at varying speeds, and landing accuracy was confirmed through static and dynamic landing experiments. The experimental results show that the proposed scheme has good dynamic tracking and landing performance.

A trans-medium aircraft is a new concept aircraft that can both dive in the water and fly in the air. In this paper, a new type of water–air multi-medium span vehicle is designed based on the water entry and exit structure model of a multi-rotor UAV. Based on the designed structural model of the cross-media aircraft, the OpenFOAM open source numerical platform is used to analyze the single-medium aerodynamic characteristics and the multi-medium spanning flow analysis. The rotating flow characteristics of single-medium air rotor and underwater propeller are calculated by sliding mesh. In order to prevent the numerical divergence caused by the deformation of the grid movement, the overset grid method and the multiphase flow technology are used for the numerical simulation of the water entry and exit of the cross-medium aircraft. Through the above analysis, the flow field characteristics of the trans-medium vehicle in different media are verified, and the changes in the body load and attitude at different water entry angles are also obtained during the process of medium crossing.

The problem of aircraft entering and exiting water is a complex, nonlinear, strongly disturbed, and multi-coupled multiphase flow problem, which involves the precise capture of the air/water interface and the multi-coupling interaction between aircraft, water, and air. Moreover, due to the large difference in medium properties during the crossing, the load on the body will suddenly change. In this paper, the VOF (volume of fluid) algorithm is used to capture the liquid surface at the air/water interface, and since body movement is involved in this process, the overset grid technology is used to avoid the traditional dynamic grid deformation problem. In the process of this numerical simulation prediction, the effects of different water-entry angles and different water-entry heights on the body load and attitude of the trans-medium aircraft, as well as the cavitation evolution law of the body water entry are analyzed. On this basis, to simulate the authenticity and complexity of the water-entry environment, numerical wave-making technology was introduced to analyze the water-entry load, posture, and cavitation evolution law of the body under different wave environments. The numerical parameters under the condition of wave and no wave are compared, and the difference in water-entry performance under the condition of wave and no wave is analyzed.

Recently, numerous new meta-heuristic algorithms have been proposed for solving optimization problems. According to the Non-Free Lunch theorem, we learn that no single algorithm can solve all optimization problems. In order to solve industrial engineering design problems more efficiently, we, inspired by the algorithm framework of the Arithmetic Optimization Algorithm (AOA) and the Harris Hawks Optimization (HHO), propose a novel hybrid algorithm based on these two algorithms, named EAOAHHO in this paper. The pinhole imaging opposition-based learning is introduced into the proposed algorithm to increase the original population diversity and the capability to escape from local optima. Furthermore, the introduction of composite mutation strategy enhances the proposed EAOAHHO exploitation and exploration to obtain better convergence accuracy. The performance of EAOAHHO is verified on 23 benchmark functions and the IEEE CEC2017 test suite. Finally, we verify the superiority of the proposed EAOAHHO over the other advanced meta-heuristic algorithms for solving four industrial engineering design problems.

Due to the large volume of pipeline transportation, low cost, safety and the reliability, and automatic control, it is widely used in many fields of industrial development and human daily life. Most of the traditional hydraulic pipelines are steel pipes, and their structure is simple. High resistance and high consumption during transportation are not conducive to the sustainable development of society. However, the human vascular system is intricate and has excellent mechanical properties. Built on the review, research on the fluid-solid coupling characteristics of a single bionic pipeline and piping system was carried out. In order to simulate the mechanical characteristics of a fluid conveying pipeline, a fluid-structure coupling model of equation 14 of a single pipeline and the transfer matrix of the pipeline system were established. The mechanical characteristics of the pipeline are studied, and the formula is calculated. The simulation analysis shows that the axial force and flow resistance decrease first and then stabilize with the increase of frequency. Finally, the experimental verification and the results show that the method is both reasonable and effective, because the simulation curve and the experimental curve are consistent in trend.