Search Results (895)

In this paper, a hierarchical optimization framework combining Bayesian and pseudospectral approaches is developed to solve the challenging problem of hybrid trajectory planning for energy-augmented hypersonic skip–glide vehicles that have plane symmetry. Traditional trajectory optimization methods usually deal with discrete energy injection timing and continuous flight control variables separately, yielding suboptimal solutions. To achieve global optimality, this proposed framework optimizes the discrete and continuous variables simultaneously, conducting Bayesian optimization for discrete global search and hp-adaptive pseudospectral algorithm for local continuous optimization. A rigorous dynamic model, considering Earth’s oblateness, rotation, aerodynamic interactions, and thrust dynamics, is established to ensure high-fidelity trajectory simulation. Numerical simulation through three representative tests indicates significant improvements: The hp-adaptive pseudospectral method achieves over 20% higher computational efficiency and accuracy compared to standard pseudospectral methods. Bayesian optimization demonstrates rapid global convergence within 22 iterations, achieving the optimal single augmentation timing that enhances flight range by up to 55.08%. Further, comprehensive joint optimization with double energy augmentation yields an additional 7.5% range extension compared to randomly selected augmentation timings. The results verify that the proposed hierarchical framework substantially improves the planned trajectory performance and adaptability to the skip–glide trajectories with hybrid maneuver. Full article

Accurate trajectory control during atmospheric entry is critical for the success of Mars landing missions, where strong non-linearities and uncertain dynamics pose significant challenges to conventional control strategies. This study develops a computational framework that integrates fuzzy parameter-varying models with Lyapunov-based analysis to achieve robust trajectory stabilization of Mars entry vehicles. The non-linear longitudinal dynamics are reformulated via sector-bounded approximation into a Takagi–Sugeno fuzzy parameter-varying model, enabling systematic gain-scheduled controller synthesis. To reduce the conservatism typically associated with quadratic Lyapunov functions, a fuzzy Lyapunov function approach is adopted, in conjunction with the Full-Block S-procedure, to derive less restrictive stability conditions expressed as linear matrix inequalities. Based on this formulation, several controllers are designed to accommodate the variations in atmospheric density and flight conditions. The proposed methodology is validated through numerical simulations, including Monte Carlo dispersion and parametric sensitivity analyses. The results demonstrate improved stability, faster convergence, and enhanced robustness compared to existing fuzzy control schemes. Overall, this work contributes a systematic and less conservative control design methodology for aerospace applications operating under severe non-linearities and uncertainties. Full article

To enable safe cooperative flight of multi-UAV formations in urban 3-D airspace with wind-field disturbances, we develop an integrated planning-control framework.The planning layer uses an APF-guided RRT* with continuous collision prediction and explicit velocity/acceleration limits, and compensates wind online.The control layer adopts a dual-loop MA-AADRC-SMC design. An adaptive ESO estimates disturbances for feed-forward cancellation, and an SMC term improves robustness and tracking accuracy. By coupling the planned trajectory with speed-weighted repulsive fields, the framework coordinates path and attitude in closed loop, enabling collision-free and overshoot-free formation flight in wind and clutter. Simulations show higher tracking accuracy and better formation stability than ADRC, PID and SMC. A Lyapunov analysis proves uniform boundedness and asymptotic stability. The framework is scalable to applications such as disaster assessment and urban air transport. Full article

In this paper, we present the design and control of a novel aerial vehicle inspired by the biomechanics of a rabbit named “Flybbit”. Flybbit consists of two main components, namely a movable “Ears” part and a rigid “Body” part, forming a composite flying system with five controllable degrees of freedom (DOFs). The “Ears” part is equipped with two tiltable motors paired with optional-sized propellers, enabling additional thrust generation and flight stability maintenance, and the “Body” part incorporates four fixed motors, analogous to a rabbit’s limbs, to provide the primary propulsion. To fully exploit the actuation capability, we derive the system dynamics and introduce a dynamic control allocation method with an adaptive strategy to mitigate actuator saturation during complex combined maneuvers. Furthermore, we analyze the differential flatness property and develop a nonlinear inverse dynamics controller enhanced with hybrid external wrench estimation, enabling accurate trajectory tracking in five DOFs. Flybbit supports both manual operation via RC and autonomous flight via onboard computation. Comprehensive simulations and real-world experiments validate the proposed design and control framework. Full article

This study presents the configuration design and attitude control of a moving-mass coaxial dual-rotor UAV (MMCDRUAV) for indoor applications. Compared with existing configurations, the proposed configuration avoids additional actuation mass and improves the control authority. Based on these improvements, a promising micro UAV platform with a high payload ability for agile indoor flight could be developed. Ground validation tests demonstrated its maneuverability, as provided by a moving-mass control (MMC) module requiring only the repositioning of existing components (e.g., battery packs) as movable masses. For trajectory tracking, an adaptive backstepping active disturbance rejection controller (ADRC) is proposed. The architecture integrates extended-state observers (ESOs) for disturbance estimation, parameter-adaptation laws for uncertainty compensation, and auxiliary systems to address control saturation. Lyapunov stability analysis proved the existence of uniformly ultimately bounded (UUB) closed-loop tracking errors. The results of the ground verification experiment confirmed enhanced tracking performance under real-world disturbances. Full article

The large-scale trajectory simulation serves as a fundamental basis for the mission planning of a rocket-powered vehicle swarm. However, the traditional flight trajectory calculation method for a rocket-powered vehicle, which employs strict dynamic and kinematic models, often struggles to meet the temporal requirements of mission planning. To address the challenges of timely computation and intelligent optimization, a segmented training strategy, derived from the domain knowledge of the multi-stage flight characteristics of a rocket-powered vehicle, is integrated into the deep neural network (DNN) method. A high-precision trajectory prediction model that fuses multi-DNN is proposed, which can rapidly generate high-precision trajectory data without depending on accurate dynamic models. Based on the determination of the characteristic parameters derived from rocket-powered trajectory theory, a homemade dataset is constructed through a traditional computation method and utilized to train the DNN model. Extensive and varying numerical simulations are given to substantiate the predictive accuracy, adaptability, and stability of the proposed DNN-based method, and the corresponding comparative tests further demonstrate the effectiveness of the segmented strategy. Additionally, the real-time computational capability is also confirmed by computing the simulation of generating full trajectory data. Full article

This paper aims to present a set of possible transfer trajectories for a rendezvous mission with asteroid 2024 YR4, using a spacecraft propelled by a photonic solar sail. Asteroid 2024 YR4 was discovered in late December 2024 and was briefly classified as Torino Scale 3 for three weeks in early 2025, before being downgraded to zero at the end of February. In this study, rapid Earth-to-asteroid transfers are analyzed by solving a typical optimal control problem, in which the thrust vector generated by the solar sail is modeled using the optical force approach. Numerical simulations are carried out assuming a low-to-medium performance solar sail, considering both a simplified orbit-to-orbit transfer and a more accurate scenario that incorporates the actual ephemerides of the celestial bodies. The numerical results indicate that a medium-performance solar sail can reach asteroid 2024 YR4, achieving the global minimum flight time and arriving before its perihelion passage in late December 2032. Full article

A Multimode Propulsion System (MPS) is an innovative spacecraft thruster concept that integrates two or more propulsion modes sharing the same type of propellant. A spacecraft equipped with an MPS can potentially combine the advantages of continuous-thrust electric propulsion and medium-to-high-thrust chemical propulsion within a single vehicle, while reducing the overall mass compared to traditional configurations where each propulsion system uses a different propellant. This feature makes the MPS concept particularly attractive for small spacecraft, such as the well-known CubeSats, which have now reached a high level of technological maturity and are employed not only in geocentric environments but also in interplanetary missions as support elements for conventional deep-space vehicles. Within the MPS framework, a Monopropellant-Electrospray Multimode Propulsion System (MEMPS) represents a specific type of micropropulsion technology that enables a single miniaturized propulsion unit to operate in either catalytic-chemical or electrospray-electric mode. This paper investigates the flight performance of a MEMPS-equipped CubeSat in a classical circle-to-circle orbit-raising (or lowering) maneuver within a two-dimensional mission scenario. Specifically, the study derives the optimal guidance law that allows the CubeSat to follow a transfer trajectory optimized either for minimum flight time or minimum propellant consumption, starting from a parking orbit of assigned radius and targeting a final circular orbit. Numerical simulations indicate that a heliocentric orbit raising, increasing the initial solar distance by $20\%$, can be achieved with a flight time of approximately 11 months and a propellant consumption slightly below 6 kg. The proposed method is applied to a heliocentric case study, although the procedure can be readily extended to geocentric transfer missions, which represent a more common application scenario for current CubeSat-based scientific missions. Full article

Linn Tonstad’s paper, ‘(Un)wise Theologians’, identifies a theological approach that puts pressure on its ability to handle its materiality sufficiently in a number of ways. However, following the trajectory of Tonstad’s discovery of “the deformations to which theology is susceptible in the university” and elsewhere, a supplementation is required to specify where its thesis needs more rigorous development. Firstly, the paper’s argument locates what Tonstad describes as “self-securitization and self-assertion” in a form of a subjectivity characterisable as a docility making possessive form of divine givenness, and it draws the papal encyclical Fides et Ratio into Tonstad’s critique of the theology of John Webster to make this case. Secondly, Tonstad’s appeal to the reparative mode of contextualisation necessitates a differentiation to be made between modes of what is commonly called ‘contextual theology’ since there are forms that shelter under this umbrella term that echo the subjectivity of that which Tonstad uncompromisingly critiques. Thirdly, while ‘(Un)wise Theologians’ only lightly indexes a reparative direction properly “chastened” theology, a kenotically interrogative sensibility may prove to be sufficiently capacious for the critical conduct of “theological therapy”. If so, then it can function to constantly trouble the theological in an appropriate manner without flight into a premature dematerialised fixation point. Full article

The pre-courtship behavior of Proholopterus chilensis on Nothofagus obliqua trees was recorded for the first time, documenting a putative female “calling” behavior and the consequent male “oriented search,” enabling the description of behavioral units, sequences, frequencies, and degrees of stereotypy. Post-resting activity in both sexes began with walking and grooming during the first hour of the scotophase, following a period of daytime inactivity. Subsequently, females extended their ovipositor both horizontally and vertically, alternating between contact with the tree substrate and, simultaneously, walking the surface (=putative calling behavior), while males became active, extending their antennae perpendicularly to the longitudinal body axis. In response to the putative call, males exhibited oriented flight and hasty walking that followed the trajectory and direction previously taken by females on the substrate, ultimately leading to their location. Statistical analysis of behavioral sequences and the stereotypy index indicated that both behaviors were non-random and partially stereotyped. These findings are consistent with previous chemical analyses of female aerations and terminalia performed by our research group, which identified semiochemicals likely functioning as long-range sex pheromones guiding males to the vicinity of the female’s tree, as well as potential trail pheromones facilitating close-range localization. This dual signaling system seems necessary to the high mobility displayed by females during calling behavior, characterized by frequent and extended bidirectional vertical walks along the trunk, which may enhance signal dispersal and/or reduce predation risk. If confirmed, this would represent a novel sexual encounter mechanism within Cerambycidae. Full article

The increasing demand for efficient aviation navigation system inspections has led to the use of Unmanned Aerial Vehicles (UAVs) as a flexible and cost-effective alternative to traditional manned aircraft. This study emphasizes the operational advantages of UAVs in transforming flight inspections, including Non-Directional Beacon (NDB) calibration. Following the successful performance evaluation of an NDB system in Banská Bystrica, Slovakia, using a manned aircraft, a UAV was deployed on the same flight path to validate its ability to replicate the procedure in terms of trajectory only, without performing any signal measurement. The UAV maintained accurate flight paths and continuous communication throughout the mission. A specialized rotatory system, operating at 868 MHz, enabled real-time tracking and ensured stable communication over long distances. The manned aircraft test revealed a maximum bearing deviation of 13.47° at 3.37 NM and a minimum received signal strength of −90 dBm, which approaches the ICAO threshold for en route navigation (±10°) but remains usable for diagnostic purposes. The UAV flight did not include signal capture but successfully completed the 40 NM profile with a circular error probable (CEP95) of 2.8 m and communication link uptime of 99.8%, confirming that the vehicle can meet procedural trajectory fidelity. These findings support the feasibility of UAV-based NDB inspections and provide the foundation for future test phases with onboard signal monitoring systems. Full article

This study proposes a hierarchical composite adaptive sliding-mode control strategy to address the strong nonlinear dynamics of a hexarotor Unmanned Aerial Vehicle (UAV) and the external disturbances encountered during flight. First, within the position-control loop, a Terminal Sliding Mode Control (TSMC) is designed to guarantee finite-time convergence of the system states, thereby significantly improving the UAV’s rapid response to complex trajectories. Concurrently, an online Adaptive rates mechanism is introduced to estimate and compensate unknown disturbances and modeling uncertainties in real time, further enhancing disturbance rejection. In the attitude-control loop, a Super-twisting Sliding Mode Control (STSMC) method is employed, where an Adaptive rate law dynamically adjusts the sliding gain to prevent overestimation and high-frequency chattering, while ensuring fast convergence and smooth response. To comprehensively validate the feasibility and superiority of the proposed scheme, a representative helical trajectory-tracking experiment was conducted and systematically compared, via simulation, against conventional control methods. Experimental results demonstrate that the proposed approach achieves stable control within 0.15 s, with maximum position and attitude tracking errors of 0.05 m and 0.15°, respectively. Moreover, it exhibits enhanced robustness and adaptability to external disturbances and parameter uncertainties, effectively improving the motion-control performance of hexacopter UAVs in complex missions. Full article

This study introduces an innovative refinement to EKF-based monocular SLAM by incorporating attitude, altitude, and range-to-base data to enhance system observability and minimize drift. In particular, by utilizing a single range measurement relative to a fixed reference point, the method enables unmanned aerial vehicles (UAVs) to mitigate error accumulation, preserve map consistency, and operate reliably in environments without GPS. This integration facilitates sustained autonomous navigation with estimation error remaining bounded over extended trajectories. Theoretical validation is provided through a nonlinear observability analysis, highlighting the general benefits of integrating range data into the SLAM framework. The system’s performance is evaluated through both virtual experiments and real-world flight data. The real-data experiments confirm the practical relevance of the approach and its ability to improve estimation accuracy in realistic scenarios. Full article

The primary challenge that robots face in disaster rescue is to precisely and efficiently construct disaster maps and achieve autonomous navigation. This paper proposes a method for air–ground collaborative map construction. It utilizes the flight capability of an unmanned aerial vehicle (UAV) to achieve rapid three-dimensional space coverage and complex terrain crossing for rapid and efficient map construction. Meanwhile, it utilizes the stable operation capability of an unmanned ground vehicle (UGV) and the ground detail survey capability to achieve precise map construction. The maps constructed by the two are accurately integrated to obtain precise disaster environment maps. Among them, the map construction and positioning technology is based on the FAST LiDAR–inertial odometry 2 (FAST-LIO2) framework, enabling the robot to achieve precise positioning even in complex environments, thereby obtaining more accurate point cloud maps. Before conducting map fusion, the point cloud is preprocessed first to reduce the density of the point cloud and also minimize the interference of noise and outliers. Subsequently, the coarse and fine registrations of the point clouds are carried out in sequence. The coarse registration is used to reduce the initial pose difference of the two point clouds, which is conducive to the subsequent rapid and efficient fine registration. The coarse registration uses the improved sample consensus initial alignment (SAC-IA) algorithm, which significantly reduces the registration time compared with the traditional SAC-IA algorithm. The precise registration uses the voxelized generalized iterative closest point (VGICP) algorithm. It has a faster registration speed compared with the generalized iterative closest point (GICP) algorithm while ensuring accuracy. In reinforcement learning navigation, we adopted the deep deterministic policy gradient (DDPG) path planning algorithm. Compared with the deep Q-network (DQN) algorithm and the A* algorithm, the DDPG algorithm is more conducive to the robot choosing a better route in a complex and unknown environment, and at the same time, the motion trajectory is smoother. This paper adopts Gazebo simulation. Compared with physical robot operation, it provides a safe, controllable, and cost-effective environment, supports efficient large-scale experiments and algorithm debugging, and also supports flexible sensor simulation and automated verification, thereby optimizing the overall testing process. Full article

Unmanned Aerial Vehicles (UAVs) exhibit significant potential in enhancing the wireless communication coverage and service quality of Mobile Edge Computing (MEC) systems due to their superior flexibility and ease of deployment. However, the rapid growth of tasks leads to transmission queuing in edge networks, while the uneven distribution of user nodes and services causes network load imbalance, resulting in increased user waiting delays. To address these issues, we propose a multi-UAV collaborative MEC network model based on Non-Orthogonal Multiple Access (NOMA). In this model, UAVs are endowed with the capability to dynamically offload tasks among one another, thereby fostering a more equitable load distribution across the UAV swarm. Furthermore, the integration of NOMA is strategically employed to alleviating the inherent queuing delays in the communication infrastructure. Considering delay and energy consumption constraints, we formulate a task offloading strategy optimization problem with the objective of minimizing the overall system delay. To solve this problem, we design a delay-optimized offloading strategy based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. By jointly optimizing task offloading decisions and UAV flight trajectories, the system delay is significantly reduced. Simulation results show that, compared to traditional approaches, the proposed algorithm achieves a delay reduction of 20.2%, 9.8%, 17.0%, 12.7%, 15.0%, and 11.6% under different scenarios, including varying task volumes, the number of IoT devices, UAV flight speed, flight time, IoT device computing capacity, and UAV computing capability. These results demonstrate the effectiveness of the proposed solution and offloading decisions in reducing the overall system delay. Full article