Search Results (8)

This study achieves a 30.8% mass reduction in amphibious UAV rotary arms via additive manufacturing-constrained topology optimization (AM-constrained TO), establishing lightweight design as the primary objective. To evaluate structural efficiency, we systematically compare three strategies: AM-constrained TO, Hexagonal Honeycomb infill (HC), and central lightening holes (ES). All configurations target comparable mass reduction. Using the SIMP method with manufacturing constraints, TO designs were generated. FEA and tensile tests evaluated stiffness, strength, failure modes, and Specific Energy Absorption (SEA). The key innovation lies in the TO approach: It achieves the primary objective of 30.8% mass reduction while simultaneously enhancing structural integrity and outperforming HC, ES, and Solid Baseline (SB) configurations in stiffness (2234 ± 76 MPa), Specific Energy Absorption (742 ± 29 J/m³), and stress distribution uniformity. The HC configuration shows progressive collapse but has the lowest stiffness (886 ± 17 MPa) and SEA (432 ± 5 J/m³) due to FDM inter-layer bonding limits. The ES configuration has the second-highest tensile strength (19.489 ± 0.19 MPa), but stress concentration around the hole reduces energy absorption, resulting in lower SEA (620 ± 15 J/m³) than TO. Full article

The arithmetic optimization algorithm (AOA) is a recently proposed swarm intelligence optimizer with a simple structure and few control parameters. However, the original AOA relies on a single update mechanism, which often leads to premature convergence and limited adaptability in complex optimization problems. To address these limitations, this paper proposes a multi-strategy improved arithmetic optimization algorithm (IAOA). The proposed algorithm constructs a heterogeneous strategy pool composed of six search strategies, including arithmetic update, differential evolution operators, competitive elite learning, interpolation-based acceleration, and curriculum education learning. Furthermore, an adaptive strategy regulation mechanism based on fitness improvement contribution is introduced to dynamically adjust the selection probability of each strategy. Extensive experiments conducted on the CEC2017 and CEC2022 benchmark suites demonstrate that IAOA achieves a superior optimization accuracy, convergence speed, and stability compared with several classical algorithms, recent metaheuristics, and AOA variants. Statistical tests including the Wilcoxon rank-sum test and Friedman mean rank test confirm the significance of the performance improvements. In addition, the algorithm is successfully applied to a three-dimensional path planning problem for amphibious unmanned aerial vehicles, demonstrating its effectiveness in solving complex engineering optimization problems. Full article

With the increasing application of unmanned aerial vehicle (UAV) in multiple fields, the path planning problem has become a key challenge in the optimization domain. This paper proposes an Improved Artificial Lemming Algorithm (IALA), which incorporates three strategies: the optimal information retention strategy based on individual historical memory, the hybrid search strategy based on differential evolution operators, and the local refined search strategy based on directed neighborhood perturbation. These strategies are designed to enhance the algorithm’s global exploration and local exploitation capabilities in tackling complex optimization problems. Subsequently, comparative experiments are conducted on the CEC2017 benchmark suite across three dimensions (30D, 50D, and 100D) against eight state-of-the-art algorithms proposed in recent years, including SBOA and DBO. The results demonstrate that IALA achieves superior performance across multiple metrics, ranking first in both the Wilcoxon rank-sum test and the Friedman ranking test. Analyses of convergence curves and data distributions further verify its excellent optimization performance and robustness. Finally, IALA and the comparative algorithms are applied to eight 3D UAV path planning scenarios and two amphibious UAV path planning models. In the independent repeated experiments across the eight scenarios, IALA attains the optimal performance 13 times in terms of the two metrics, Mean and Std. It also ranks first in the Monte Carlo experiments for the two amphibious UAV path planning models. Full article

In response to the challenges faced by unmanned aerial vehicles (UAV) in cluttered environments such as forests, ruins, and pipelines, this study introduces a ground–air amphibious UAV specifically designed for personnel search and rescue in complex environments. By innovatively designing and applying a separation cage structure, the UAV’s capabilities for ground movement and aerial flight have been enhanced, effectively overcoming the limitations of traditional single-mode robots operating in narrow or obstacle-dense areas. This design addresses the occlusion issue of sensing components in traditional caged UAVs while maintaining protection for both the UAV itself and the surrounding environment. Additionally, through the innovative design of an H-shaped quadcopter frame skeleton structure, the UAV has gained the ability to perform steady-state aerial flight while also better adapting to the separation cage structure, achieving a reduced energy consumption and significantly improving its operational capabilities in complex environments. The experimental results demonstrate that the UAV prototype, weighing 1.2 kg with a 1 kg payload capacity, achieves a 40 min maximum endurance under full payload conditions at the endurance speed of 10 m/s while performing real-time object detection. The system reliably executes multimodal operations, including stable takeoff, landing, aerial hovering, directional maneuvering, and terrestrial locomotion with coordinated steering control. Full article

This paper presents a study on controlling the out-of-water motion of amphibious multi-rotor UAVs using a cascade control method based on the Active Disturbance Rejection Control (ADRC) algorithm. The aim is to overcome the challenges of time-varying model parameters and complex external disturbances. The research involves developing an underwater dynamic model and analyzing hydrodynamic forces to calculate theoretical inertial hydrodynamic forces and simulate viscous hydrodynamic forces. This establishes the relationship between viscous hydrodynamic forces and exit velocity. A complete air dynamic model is then established, selecting model parameters based on the center of mass position of the amphibious vehicle to enable switching from water to air. To address control algorithm instability caused by changes in model parameters, position and attitude controllers are built using the ADRC algorithm. The control effects are compared with traditional PID and sliding mode controllers (SMC) to verify the effectiveness and superiority of the proposed cascade ADRC control strategy. Experimental results show that our controller has stronger anti-interference than traditional PID and SMC controllers and can overcome control instability caused by changes in model parameters. Our research highlights the importance of using ADRC-based controllers for amphibious multi-rotor UAVs to achieve robust and stable control. Full article

Recent large-scale operations, including frequent maritime transportation and unauthorised as well as unlawful collisions of drainage wastes, have polluted the ocean’s ecology. Due to the ocean’s unsuitable ecology, the entire globe may experience drastic aberrant conditions, which will force illness onto all living things. Therefore, an advanced system is very necessary to remove the undesired waste from the ocean’s surface and interior. Through the use of progressive unmanned amphibious vehicles (UAV), this study provides a dynamic operational mode-based solution to damage removal. In order to successfully handle the heavy payloads of ravage collections when the UAV reveals centre of gravity concerns, a highly manoeuvrable-based design inspired by nature has been imposed. The ideal creatures to serve as the inspiration for this piece are tropical birds, which have a long tail for navigating tricky situations. The design initialization was carried out by focusing on the outer body of tropical birds. Following this, special calculations were conducted and the full design parameters of the UAV were established. This study proposes a unique mathematical formulation for the development of primary and secondary design parameters of an UAV. The proposed mission profile of this application is computationally tested with the aid of sophisticated computational methodologies after the modelling of this UAV. The computational methods that are required are one-way coupling-based hydro-structural interaction assessments and computational hydrodynamic analyses. Computing is used to determine the aerodynamic and hydrodynamic forces over the UAV, the lightweight materials to withstand high fluid dynamic loads, and the buoyancy forces to complete the UAV components. These computational methods have been used to produce a flexible and fine-tuned UAV design for targeted real-time applications. Full article

In recent years, fishery has developed rapidly. For the vital interests of the majority of fishermen, this paper makes full use of Internet of Things and air–water amphibious UAV technology to provide an integrated system that can meet the requirements of fishery water quality monitoring and prediction evaluation. To monitor target water quality in real time, the water quality monitoring of the system is mainly completed by a six-rotor floating UAV that carries water quality sensors. The GPRS module is then used to realize remote data transmission. The prediction of water quality transmission data is mainly realized by the algorithm of time series comprehensive analysis. The evaluation rules are determined according to the water quality evaluation standards to evaluate the predicted water quality data. Finally, the feasibility of the system is proved through experiments. The results show that the system can effectively evaluate fishery water quality under different weather conditions. The prediction accuracy of the pH, dissolved oxygen content, and ammonia nitrogen content of fishery water quality can reach 99%, 98%, and 99% on sunny days, and reach 92%, 98%, and 91% on rainy days. Full article

Unmanned aerial vehicles (UAVs) have gained significant attention in recent times due to their suitability for a wide variety of civil, military, and societal missions. Development of an unmanned amphibious vehicle integrating the features of a multi-rotor UAV and a hovercraft is the focus of the present study. Components and subsystems of the amphibious vehicle are developed with due consideration for aerodynamic, structural, and environmental aspects. Finite element analysis (FEA) on static thrust conditions and skirt pressure are performed to evaluate the strength of the structure. For diverse wind conditions and angles of attack (AOA), computational fluid dynamic (CFD) analysis is carried out to assess the effect of drag and suitable design modification is suggested. A prototype is built with a 7 kg payload capacity and successfully tested for stable operations in flight and water-borne modes. Internet of things (IoT) based water quality measurement is performed in a typical lake and water quality is measured using pH, dissolved oxygen (DO), turbidity, and electrical conductivity (EC) sensors. The developed vehicle is expected to meet functional requirements of disaster missions catering to the water quality monitoring of large water bodies. Full article