Search Results (116)

Multi-vessel formation shipping demonstrates significant potential for enhancing maritime transportation efficiency and economy. However, existing route planning systems inadequately address the unique challenges of formations, where traditional methods fail to integrate global optimality, local dynamic obstacle avoidance, and formation coordination into a cohesive system. Global planning often neglects multi-ship collaborative constraints, while local methods disregard vessel maneuvering characteristics and formation stability. This paper proposes GLFM, a three-layer hierarchical framework (global optimization–local adjustment-formation collaboration module) for intelligent route planning of transport ship formations. GLFM integrates an improved multi-objective A* algorithm for global path optimization under dynamic meteorological and oceanographic (METOC) conditions and International Maritime Organization (IMO) safety regulations, with an enhanced Artificial Potential Field (APF) method incorporating ship safety domains for dynamic local obstacle avoidance. Formation, structural stability, and coordination are achieved through an improved leader–follower approach. Simulation results demonstrate that GLFM-generated trajectories significantly outperform conventional routes, reducing average risk level by 38.46% and voyage duration by 12.15%, while maintaining zero speed and period violation rates. Effective obstacle avoidance is achieved, with the leader vessel navigating optimized global waypoints and followers maintaining formation structure. The GLFM framework successfully balances global optimality with local responsiveness, enhances formation transportation efficiency and safety, and provides a comprehensive solution for intelligent route optimization in multi-constrained marine convoy operations. Full article

Oyster aquaculture in the U.S. faces severe inefficiencies due to the absence of precise path planning tools, resulting in environmental degradation and resource waste. Current dredging techniques lack trajectory planning, often leading to redundant seabed disturbance and suboptimal shell distribution. Existing vessel models—such as the Nomoto or Dubins models—are not designed to map steering inputs directly to spatial coordinates, presenting a research gap in maneuver planning for underactuated boats. This research fills that gap by introducing a novel hybrid vessel kinetics model that integrates the Nomoto model with Dubins motion primitives. Our approach links steering inputs directly to the vessel motion, enabling Cartesian coordinate path generation without relying on intermediate variables like yaw velocity. Field trials in the Chesapeake Bay demonstrate consistent trajectory following performance across varied path complexities, with average offsets of 0.01 m, 1.35 m, and 0.42 m. This work represents a scalable, efficient step toward real-time, constraint-aware automation in oyster harvesting, with broader implications for sustainable aquaculture operations. Full article

During the process of flexible aerial refueling, the flexible structure of the hose drogue assembly is affected by internal and external interference, such as docking maneuvering, deformation of the hose, attitude changes, and body vibrations, causing the hose to swing and the whipping phenomenon, which greatly limits the success rate and safety of aerial refueling operations. Based on a 2.4 m transonic wind tunnel, high-speed wind tunnel test technology of a flexible aerial refueling hose–drogue system was established to carry out experimental research on the coupling characteristics of aerodynamics and multi-body dynamics. Based on the aid of Videogrammetry Model Deformation (VMD), high-speed photography, dynamic balance, and other wind tunnel test technologies, the dynamic characteristics of the hose–drogue system in a high-speed airflow and during the approach of the receiver are obtained. Adopting flexible multi-body dynamics, a dynamic system of the tanker, hose, drogue, and receiver is modeled. The cable/beam model is based on an arbitrary Lagrange–Euler method, and the absolute node coordinate method is used to describe the deformation, movement, and length variation in the hose during both winding and unwinding. The aerodynamic forces of the tanker, receiver, hose, and drogue are modeled, reflecting the coupling influence of movement of the tanker and receiver, the deformation of the hose and drogue, and the aerodynamic forces on each other. The tests show that during the approach of the receiver (distance from 1000 mm to 20 mm), the sinking amount of the drogue increases by 31 mm; due to the offset of the receiver probe, the drogue moves sideways from the symmetric plane of the receiver. Meanwhile, the oscillation magnitude of the drogue increases (from 33 to 48 and from 48 to 80 in spanwise and longitudinal directions, respectively). The simulation results show that the shear force induced by the oscillation of the hose and the propagation velocity of both the longitudinal and shear waves are affected by the hose stiffness and Mach number. The results presented in this work can be of great reference to further increase the safety of aerial refueling. Full article

For unmanned aerial vehicles with long-duration autonomous missions, efficient energy management is critically important. One of the most promising solutions is solar power, the implementation of which requires the continuous orientation tracking of the Sun’s position. This study presents a three-axis active solar tracking system based on a gimbal mount, providing full kinematic control of the panel in space. A mathematical model of orientation is developed using the Earth-Centered Inertial, local geographic frame, and unmanned aerial vehicle body coordinate systems. An aerodynamic analysis is conducted, including a quantitative assessment of drag, lift, and torque on the panel. Based on the obtained characteristics, limiting conditions for the safe operation of the tracker are formulated. An adaptive control algorithm is introduced, minimizing a generalized objective function that accounts for angular deviation, aerodynamic loads, and current energy balance. Numerical simulations are described, demonstrating system stability under various scenarios: turbulence, maneuvers, power limitations, and sensor errors. The results confirm the effectiveness of the proposed approach under real-world operating conditions. Full article

This paper addresses the challenge of ineffective coordination between terminal maneuvering and precision strike capabilities in hypersonic unmanned aerial vehicles (UAVs). To resolve this issue, an intelligent spiral maneuver trajectory generation method utilizing a virtual trajectory framework is proposed. Initially, a relative motion model between the UAV and the virtual center of mass (VCM) is established based on the geometric principles of the Archimedean spiral. Subsequently, the interaction dynamics between the VCM and the target are formulated as a Markov decision process (MDP). A deep reinforcement learning (DRL) approach, employing the proximal policy optimization (PPO) algorithm, is implemented to train a policy network capable of end-to-end virtual trajectory generation. Ultimately, the relative spiral motion is superimposed onto the generated virtual trajectory to synthesize a composite spiral maneuvering trajectory. The simulation results demonstrate that the proposed method achieves expansive spiral maneuvering ranges while ensuring precise target strikes. Full article

Maintaining a spacecraft’s center of mass at the origin of a body-fixed coordinate system is often key to precision trajectory tracking. Typically, the inertia matrix is estimated and verified with preliminary ground testing. This article presents groundbreaking preliminary results and significant findings from on-orbit space experiments validating recently proposed methods as part of a larger study over multiple years. Time-varying estimates of inertia moments and products are used to reveal time-varying estimates of the location of spacecraft center of mass using geosynchronous orbiting test satellites proposing a novel two-norm optimal projection learning method. Using the parallel axis theorem, the location of the mass center is parameterized using the cross products of inertia, and that information is extracted from spaceflight maneuver data validating modeling and simulation. Mass inertia properties are discerned, and the mass center is experimentally revealed to be over thirty centimeters away from the assumed locations in two of the three axes. Rotation about one axis is found to be very well balanced, with the center of gravity lying on that axis. Two-to-three orders of magnitude corrections to inertia identification are experimentally demonstrated. Combined-axis three-dimensional maneuvers are found to obscure identification compared with single-axis maneuvering as predicted by the sequel analytic study. Mass center location migrates 36–95% and subsequent validating experiments duplicate the results to within 0.1%. Full article

Snowboard Big Air (SBA), recognized as an Olympic discipline since 2018, emphasizes maneuver difficulty as a key scoring criterion, requiring athletes to integrate technical skill with adaptive responses to dynamic environments in order to perform complex aerial rotations. The takeoff phase is critical, determining both flight trajectory and rotational performance through coordinated lower limb extension and upper body movements. Despite advances in motion analysis technology, quantitative assessment of key takeoff parameters remains limited. This study investigates parameters related to performance, joint kinematics, and rotational kinetics during the SBA takeoff phase to identify key factors for success and provide practical guidance to athletes and coaches. Eleven athletes from the Chinese national snowboard team performed multiple backside tricks (720°, 1080°, 1440°, and 1800°) at an outdoor dry slope with airbag landings. Three-dimensional motion capture with synchronized cameras was used to collect data on performance, joint motion, and rotational kinetics during takeoff. The results showed significant increases in most measured metrics with rising trick difficulty from 720° to 1800°. The findings reveal that elite SBA athletes optimize performance in high-difficulty maneuvers by increasing the moment of inertia, maximizing propulsion, and refining joint kinematics to enhance rotational energy and speed. These results suggest that training should emphasize lower limb power, core and shoulder strength, flexibility, and coordination to maximize performance in advanced maneuvers. Full article

This paper introduces a novel approach to modeling and control system design for tugboat-assisted operations, such as the docking and rescue of marine vessels. In these scenarios, one or more tugboats push, pull, or guide large vessels to ensure precise and safe maneuvering. Their control systems ensure accurate coordination, vessel positioning, and overall stability, even in the presence of system uncertainties, imperfect control allocation, and ocean disturbances. To address these challenges, a mathematical model of a general tugboat-assisted system is first derived. Then, a new vector of variables is introduced, leading to a modified model representation where the mismatches from the allocation and lower-level tugboat controllers can be realized in the vessel’s motion equation. Thus, the design of a controller can take this aspect into account to enhance the overall system’s performance and stability. Thirdly, a control system design method is proposed, employing a centralized control framework and ensuring a mixed $H₂/H_{\infty }$ performance criterion. Finally, a case study is conducted with a particular tugboat-assisted configuration and the results validate the effectiveness of the control solution. Full article

Traditional elastic correction methods fail to address the significant aeroelastic interactions arising from unsteady flow fields and structural deformations during aggressive maneuvers. To resolve this, a numerical method is developed by solving unsteady aerodynamic equations coupled with a rigid–flexible dynamics equations derived from Lagrangian mechanics in quasi-coordinates. Validation via a flexible pendulum test and AGARD445.6 wing flutter simulations demonstrates excellent agreement with experimental data, confirming the method’s accuracy. Application to a slender air-to-air missile reveals that reducing structural stiffness can destabilize the aircraft, transitioning it from stable to unstable states during forced pitching motions. Studies on longitudinal flight under preset rudder deflection control indicate that the aeroelastic effect increases both the amplitude and period of pitch angles, ultimately resulting in larger equilibrium angles compared to a rigid-body model. The free-flight simulations highlight trajectory deviations due to deformation-induced aerodynamic forces, which emphasizes the necessity of multidisciplinary coupling analysis. The numerical results show that the proposed CFD/CSD-based coupling methodology offers a robust aeroelastic effect analysis tool for flexible flight vehicles during aggressive maneuvers. Full article

Earth observation satellites, particularly agile Earth observation satellites (AEOSs) with enhanced attitude maneuverability, have become increasingly crucial in emergency response and disaster monitoring operations. Efficient mission planning for densely distributed ground targets with diverse priorities poses significant challenges, especially when considering strict attitude maneuver constraints and time-sensitive requirements. To address these challenges, this paper proposes a target clusters and dual-timeline optimization (TCDO) framework that integrates priority-based geographical clustering with temporal–spatial coordination mechanisms for efficient mission planning. The proposed approach effectively maintains satellite maneuver constraints while achieving significant improvements in priority-based target acquisition and computational efficiency. Experimental results demonstrate the framework’s superior performance, achieving a 94% coverage rate and a 99.5% reduction in computation time compared to traditional scheduling methods, such as linear programming and genetic algorithms. Full article

Compared to traditional remote sensing technology, video satellites have unique advantages such as real-time continuous imaging and the ability to independently complete staring observation. To achieve effective staring control, the satellite needs to perform attitude maneuvers to ensure that the target’s projection stays within the camera’s visual field and gradually reaches the desired position. The generation of image-based control instructions relies on the calculation of projection coordinates and their rate of change (i.e., visual velocity) of the projection point on the camera’s image plane. However, the visual velocity is usually difficult to obtain directly. Traditional calculation methods of visual velocity using time differentials are limited by video frame rates and the computing power of onboard processors, and is greatly affected by measurement noise, resulting in decreased control accuracy and a higher consumption of maneuvering energy. In order to address the shortcomings of traditional calculations of visual speed by time difference methods, this paper proposes a control method based on the estimation of visual velocity, which achieves real-time calculation of the target’s visual speed through adaptive estimation; then, the stability of the closed-loop system is rigorously demonstrated. Finally, through simulation comparison with the traditional differential method, the results show that the proposed method has an improvement in attitude accuracy for about 74% and a reduction in energy consumption by about 77%. Full article

Targeting the autonomous decision-making problem of unmanned combat aerial vehicles (UCAVs) in a two-versus-one (2v1) within-visual-range (WVR) air combat scenario, this paper proposes a maneuver decision-making method based on tactical coordination. First, a coordinated situation assessment model is designed, which subdivides the air combat situation into optimization-driven and tactical coordinated situations. The former combines missile attack zone calculation and trajectory prediction to optimize the control quantity of a single aircraft, while the latter uses fuzzy logic to analyze the overall situation of the three aircraft to drive tactical selection. Second, a decision-making model based on a hierarchical expert system is constructed, establishing a hierarchical decision-making framework with a UCAV-coordinated combat knowledge base. The coordinated situation assessment results are used to match corresponding tactics and maneuver control quantities. Finally, an improved particle swarm optimization algorithm (I-PSO) is proposed, which enhances the optimization ability and real-time performance through the design of local social factor iterative components and adaptive adjustment of inertia weights. Air combat simulations in four different scenarios verify the effectiveness and superiority of the proposed decision-making method. The results show that the method can achieve autonomous decision making in dynamic air combat. Compared with decision-making methods based on optimization algorithms and differential games, the win rate is increased by about 17% and 18%, respectively, and the single-step decision-making time is less than 0.02 s, demonstrating high real-time performance and win rate. This research provides new ideas and methods for the autonomous decision making of UCAVs in complex air combat scenarios. Full article

This research addresses minimum-fuel pinpoint lunar landing at the South Pole, focusing on trajectory design and near-optimal guidance aimed at driving a spacecraft from a circular low lunar orbit (LLO) to an instantaneous hovering state above the lunar surface. Orbit dynamics is propagated in a high-fidelity ephemeris-based framework, which employs spherical coordinates as the state variables and includes several harmonics of the selenopotential, as well as third-body gravitational perturbations due to the Earth and Sun. Minimum-fuel two-impulse descent transfers are identified using Lambert problem solutions as initial guesses, followed by refinement in the high-fidelity model, for a range of initial LLO inclinations. Then, a feedback Lambert-based impulsive guidance algorithm is designed and tested through a Monte Carlo campaign to assess the effectiveness under non-nominal conditions related to injection and actuation errors. Because the last braking maneuver is relatively large, a finite-thrust, locally flat, near-optimal guidance is introduced and applied. Simplified dynamics is assumed for the purpose of defining a minimum-time optimal control problem along the last thrust arc. This admits a closed-form solution, which is iteratively used until the desired instantaneous hovering condition is reached. The numerical results in non-nominal flight conditions testify to the effectiveness of the guidance approach at hand in terms of propellant consumption and precision at landing. Full article

In the domain of autonomous driving systems, vehicle trajectory prediction represents a critical aspect, as it significantly contributes to the safe maneuvering of vehicles within intricate traffic environments. Nevertheless, a preponderance of extant research efforts have been chiefly centered on the spatio-temporal relationships intrinsic to the vehicle itself, thereby exhibiting deficiencies in the dynamic perception of and interaction capabilities with adjacent vehicles. In light of this limitation, we propose a vehicle trajectory prediction algorithm predicated on a hybrid prediction model. Initially, the algorithm extracts pertinent context information pertaining to the target vehicle and its neighboring vehicles through the application of a two-layer long short-term memory network. Subsequently, a fusion module is deployed to assimilate the characteristics of the temporal influence, spatial influence, and interactive influence of the surrounding vehicles, followed by the integration of these attributes. Ultimately, the prediction module is engaged to yield the predicted movement positions of the vehicles, expressed in coordinate form. The proposed algorithm was trained and validated using the publicly accessible datasets I-80 and US-101. The experimental results demonstrate that our proposed algorithm is capable of generating more precise prediction results. Full article

A global prescribed performance control method is proposed for a class of uncertain high-order odd-rational-power nonlinear systems (a chain of integrators whose power is the ratio of odd integers) with actuator faults, where the high-order odd-rational powers and the parameters of actuator faults are unknown. A new coordinate transformation on the state and tracking errors is introduced based on the tangent function and its inverse function, resulting in a global low-complexity prescribed performance controller. The proposed controller does not require any knowledge of system nonlinearities or powers, and it also does not require the time derivatives of virtual control signals without using any filters, which implies the controller is of low complexity. Finally, two simulation examples, including a practical high-maneuver flight control example, are given to demonstrate the effectiveness of our method. Full article