Search Results (1,338)

Traditional front-wheel-steering (FWS) unmanned vehicles frequently encounter maneuverability bottlenecks in confined spaces or during rapid formation changes due to inherent kinematic limitations. To mitigate these constraints, this study proposes an adaptive multi-mode (AMM) cooperative formation control framework tailored for four-wheel independent drive and steering (4WIDS) platforms. The methodology constructs a unified planner based on the virtual structure concept, integrated with an autonomous steering-mode selector. By synthesizing real-time mission requirements with longitudinal and lateral tracking errors, the system dynamically switches between crab steering, four-wheel counter-steering (4WCS), and conventional FWS modes to optimize spatial utilization. Validated within a seven-vehicle MATLAB/Simulink environment, simulation results demonstrate that the crab-steering mode significantly reduces relocation time for small lateral adjustments by eliminating redundant heading changes, whereas FWS and 4WCS modes are preferentially selected to ensure stability during high-speed or large-span maneuvers. These findings confirm that the proposed AMM strategy effectively reconciles the trade-off between agility and stability, providing a robust solution for complex cooperative maneuvering tasks. Full article

This study presents a human-navigable ship-handling support system that employs artificial intelligence (AI) for survey line tracking. AI was developed using the Deep Deterministic Policy Gradient (DDPG), a type of deep reinforcement learning (DRL), and was evaluated through experiments conducted with a research vessel. The experiments revealed several issues inherent to DRL that required improvement. The first issue was the asymmetry observed in the policy learned through the DDPG. To address this, a learning approach that utilizes symmetric training data and symmetry-constrained actor and critic neural networks was proposed. The second issue was excessive steering during tracking maneuvers. To mitigate this, an objective function for actor learning that incorporates a cost term to suppress the magnitude of actions was proposed. The third issue was the frequent oscillation of actions. To resolve this, improved conditioning for action policy smoothing was introduced in the objective function to smooth actions appropriate to the situation. A subsequent experiment at sea was conducted to evaluate the improved AI-based ship-handling support system. As a result, precise path tracking performance with minimal operator discomfort and smooth control actions was achieved through manual ship handling guided by AI-generated instructions under actual sea conditions. Full article

The Survey Camera (SC) is the key instrument of the China Space Station Telescope (CSST), with its imaging performance significantly constrained by microvibrations from internal sources such as the shutter and cryocoolers. This paper proposes a systematic microvibration suppression scheme integrating disturbance source control, payload isolation, and transfer path optimization to meet the stringent requirements. The Cryocooler Assembly (CCA) compressor adopts a symmetric piston layout and a real-time vibration cancellation algorithm to reduce the vibration. Coupled with a vibration isolator designed by combining hydraulic damping and a flexible structure, it achieves a vibration isolation efficiency of 95%. The shutter adopts dual-blade symmetric design with sinusoidal angular acceleration control, ensuring its vibrations fall within the compensable range of the Fast Steering Mirror (FSM). And the finite element optimization method is used to optimize the dynamic characteristics of the Support Structure (SST) made of M55J carbon fiber composite material, to avoid resonance in the critical frequency bands. System-level tests on the integrated SC show that the RMS values of vibration force and torque within 8–300 Hz are 0.25 N and 0.08 N·m, respectively, meeting design specifications. This scheme validates effective microvibration control, guaranteeing the SC’s high-resolution imaging capability for the CSST mission. Full article

The evolution towards 6G is set to transform Vehicle-to-Everything (V2X) networks by introducing advanced technologies such as Six-Dimensional Movable Antenna (6DMA). This technology endows Roadside Units (RSUs) with dynamic beam-steering capabilities, enabling adaptive coverage. However, traditional RSU deployment strategies, optimized for static coverage, are fundamentally mismatched with these new dynamic capabilities, leading to a critical deployment–optimization mismatch. This paper addresses this challenge by proposing DyDO, a novel Dynamic Deployment and Optimization framework for the utilization of 6DMA-RSUs. Our framework strategically decouples the problem into two modules operating on distinct timescales. On a slow timescale, an offline deployment module analyzes long-term historical traffic data to identify optimal RSU locations. This is guided by a newly proposed metric, the Dynamic Potential Score (DPS), which quantifies a location’s intrinsic value for dynamic adaptation by integrating spatial concentration, temporal volatility, and traffic magnitude. On a fast timescale, an online control module employs an efficient Sequential Angular Search (SAS) algorithm to perform real-time, adaptive beam steering based on immediate traffic patterns. Extensive experiments on a large-scale, real-world trajectory dataset demonstrate that DyDO outperforms conventional static deployment methodologies. This work highlights the necessity of dynamic-aware deployment to fully unlock the potential of 6DMA in future V2X systems. Full article

The present study aimed to evaluate whether the inclusion of curcumin as a performance enhancer in finishing cattle has positive effects on animal production, the ruminal environment, hematological and biochemical markers, as well as meat quality. Sixteen castrated Holstein steers, 8 months of age, with an average body weight of 247 ± 3.89 kg were divided into two groups: Control, consisting of animals that consumed 144 mg of monensin/animal/day (n = 8); Treatment, consisting of animals that consumed 552 mg of curcumin/animal/day (n = 8). Animals were fed a diet containing 44% roughage (corn silage) and 56% concentrate for 105 days. During this period, body weight measurements were recorded, and blood samples were collected for the determination of hematological, biochemical, and immunological variables. At the end of the experimental period, animals were slaughtered and meat samples were collected for evaluation. No differences were observed between groups for animal performance, feed intake, or feed efficiency. A lower leukocyte count (lymphocyte and granulocyte) and a higher platelet count were observed in animals that consumed curcumin. These animals also exhibited higher cholesterol levels, along with lower circulating glucose concentrations compared to the control group. In the ruminal environment, higher bacterial activity and greater protozoal counts were observed in the treatment group, but no effects on ruminal short-chain fatty acids were observed. Higher activity of the enzymes glutathione S-transferase in serum and superoxide dismutase in meat was observed, combined with lower lipid peroxidation in serum and meat. Meat from steers fed curcumin showed greater yellow color intensity, higher water-holding capacity, and a higher proportion of monounsaturated fatty acids compared to the control group. These results suggest that curcumin can be used as a performance enhancer, similar to monensin, when thinking about performance, but beyond that, curcumin triggered anti-inflammatory and antioxidant action. Full article

Amidst the surge of high-density urban development and the growing demand for high-quality spaces, the Usable Area Coefficient (UAC) has emerged as a pivotal metric in the architectural planning. The rational calibration of the UAC for primary school buildings is key to balancing intensive land use, educational demands, and the well-being of children. Taking primary schools in a district of Qingdao as the research subject, this research rationally optimizes the range of UAC by constructing an evolutionary game model, based on quantitatively analyzing the divergent perspectives and requirements of three stakeholders: the government, school administrators, and students. After further identifying the key factors that influence the ultimate decision, the study yields the following insights: (1) The incremental comprehensive benefit emerges as the linchpin influencing the UAC. (2) The government’s risk compensation to schools and the benefit-sharing coefficient between schools and students exert significant impacts on system evolution. (3) Effective control of construction and land costs, coupled with enhanced availability of open activity spaces, paves the way for consensus on low UAC. This research not only furnishes a theoretical framework and practical guidance for harmonizing land use efficiency with educational excellence but also steers the design of salubrious primary school environments and informs pertinent policy-making. Full article

Dongbei suancai is a popular traditional fermented vegetable in Northeast China. However, the conventional production methods often lead to nitrite accumulation and quality fluctuations, which to some extent constrain the development towards health and scale. To address this, a novel Direct-Vat-Set (DVS) starter was developed based on L. mesenteroides AA001, a strain isolated from traditional fermented foods and possessing high nitrite-degrading capability. By optimizing the culture medium and cryoprotectant formulation, the cell density and freeze-drying survival rate were significantly enhanced. Crucially, the freeze-drying process did not impair the core degradation function of the strain, with the nitrite degradation rate remaining above 90%. The DVS starter was applied to Dongbei suancai fermentation, effectively inhibiting nitrite accumulation while simultaneously increasing organic acid content and optimizing the proportion of essential amino acids. It simultaneously suppressed the growth of undesirable bacteria and, under low-temperature conditions, steered the microbial community toward metabolic activities, ensuring the controllability and safety of the fermentation process. Therefore, inoculation with the L. mesenteroides AA001 DVS starter effectively inhibits nitrite accumulation, enabling a highly efficient, stable, and clean fermentation process that significantly improves the quality of Dongbei suancai. Full article

To overcome the limitations in maneuverability and adaptability of traditional underwater vehicles, a novel hybrid-actuated, multimodal cephalopod-inspired robot is proposed. This robot innovatively integrates a hybrid drive system wherein sinusoidal undulating fins provide primary propulsion and steering, water-flapping tentacles offer auxiliary burst propulsion, and a gear-and-rack center-of-gravity (CoG) adjustment module modulates the pitch angle to enable depth control through hydrodynamic lift during forward motion. The effectiveness of the design was validated through a series of experiments. Thrust tests demonstrated that the undulating fin thrust scales quadratically with oscillation frequency, aligning with hydrodynamic theory. Mobility experiments confirmed the multi-degree-of-freedom control of the robot, demonstrating effective diving and surfacing via the CoG module and high maneuverability, achieving a turning radius of approximately 15 cm through differential fin control. Furthermore, field trials in an outdoor artificial lake with a depth of less than 1 m validated its environmental robustness. These results confirm the versatile maneuvering capabilities of the robot and its robust adaptability to confined and shallow-water environments, presenting a novel platform for complex underwater observation tasks. Full article

This study investigates the mechanisms of topographic steering and the resultant track morphology of typhoon-like vortices over complex terrain. Leveraging a dynamic model based on potential vorticity (PV) conservation, we conducted a comprehensive sensitivity analysis over both an idealized bell-shaped mountain and the realistic topography of Taiwan. Results indicate that a triad of controls governs track evolution: vortex intensity (α), terrain geometry ($d{h}_B^{*}/{dt}^{*}$), and interaction time (impinging angle $\gamma$). To quantify predictability, we introduce the Track Divergence Percentage ($t_d$), which partitions the phase space into distinct Track Diverging (TDZ) and Converging (TCZ) Zones. The results demonstrate that vortex intensity, terrain-induced forcing, and interaction time jointly organize a regime-dependent predictability landscape, characterized by distinct zones of track divergence and convergence separated by a dynamically balanced trajectory. This framework provides a physically interpretable explanation for why small perturbations in initial conditions can lead to qualitatively different track outcomes near complex terrain. Rather than aiming at direct forecast skill improvement, this study provides a physically interpretable diagnostic framework for understanding terrain-induced track sensitivity and uncertainty, with implications for interpreting ensemble spread in forecasting systems. Full article

Prolonged operation of cotton picker poses significant risks of work-related musculoskeletal disorders (WMSDs), primarily driven by non-ergonomic cab layouts that fail to accommodate the unique “left-hand steering, right-hand lever” operational mode. Traditional optimization methods, relying on general digital human models or isolated surface electromyography (sEMG) measurements, often lack the physiological fidelity and computational efficiency for high-dimensional, personalized design. To address this interdisciplinary challenge in agricultural engineering and ergonomics, this study proposes a novel AMS-RF-DBO framework that integrates high-fidelity biomechanical simulation with intelligent optimization. A driver–cabin biomechanical model was developed using the AnyBody Modeling System (AMS) and validated against sEMG data (ICC = 0.695). This model generated a dataset linking cab layout parameters to maximum muscle activation (MA). Using steering wheel and control lever coordinates (X, Y, Z) as inputs, a Random Forest (RF) regression model demonstrated strong performance (R² = 0.91). Optimization with the Dung Beetle Optimizer (DBO) algorithm yielded an optimal configuration: steering wheel (L1 = 434 mm, H1 = 738 mm, θ = 32°) and control lever (L2 = 357 mm, H2 = 782 mm, M = 411 mm), reducing upper-limb MA from 3.82% to 1.47% and peak muscle load by 61.5%. This study not only provides empirical support for ergonomic cab design in cotton pickers to reduce operator fatigue and health risks but also establishes a replicable technical paradigm for ergonomic optimization of other specialized agricultural machinery. Full article

Compact heavy-duty skid-steer robots are increasingly used for city logistics and intralogistics tasks where high payload capacity and stability are required. However, their limited maneuverability and non-negligible turning radius challenge conventional waypoint-tracking controllers that assume unconstrained motion. This paper proposes a curvature-constrained trajectory planning and control framework that guarantees geometrically feasible motion for such platforms. The controller integrates an explicit curvature limit into a finite-state machine, ensuring smooth heading transitions without in-place rotation. The overall architecture integrates GNSS-RTK and IMU localization, modular ROS 2 nodes for trajectory execution, and a supervisory interface developed in Foxglove Studio for intuitive mission planning. Field trials on a custom four-wheel-drive skid-steer platform demonstrate centimeter-scale waypoint accuracy on straight and curved trajectories, with stable curvature compliance across all tested scenarios. The proposed method achieves the smoothness required by most applications while maintaining the computational simplicity of geometric followers. Computational simplicity is reflected in the absence of online optimization or trajectory reparameterization; the controller executes a constant-time geometric update per cycle, independent of waypoint count. The results confirm that curvature-aware control enables reliable navigation of compact heavy-duty robots in semi-structured outdoor environments and provides a practical foundation for future extensions. Full article

To tackle the challenges faced by traditional wheeled tractors, whose steering systems have low flexibility and a large turning radius, and thus make turning hard in small fields and greenhouses, this paper proposes a differential steering control technology for battery-electric unmanned tractors. This innovative approach enables zero-radius turning while delivering environmental and economic advantages. Firstly, the system architecture and key components of the battery-electric unmanned tractor with differential steering are designed, including the mechanical structure, wheel-drive system, electrical system, and power battery. Based on the proposed system architecture, a multi-physics coupled model is established, covering the motor, reducer, battery, driver, vehicle body, and the relationship between tires and road surfaces. A multi-closed-loop control algorithm, regulating both the motor speed and yaw angular velocity of the tractor, is developed for differential steering control. The validation, conducted via a digital simulation platform, yields critical state curves for motor current, torque, speed, and vehicle rotation. This study establishes a novel theoretical framework for unmanned tractor control, with prototype development guided by the proposed methodology. Experimental validation of zero-radius steering confirms the efficacy of differential steering in battery-electric platforms. The research outcomes provide theoretical basis and technical references for advancing intelligent and electric agricultural equipment. Full article

Microwave, millimeter-wave, and terahertz devices are fundamental to modern 5G/6G communications, automotive imaging radar, and sensing systems. As essential RF front-end elements, passive microwave array components on static platforms remain constrained by fixed geometry and single-frequency excitation, leading to limited spatial resolution and weak interference suppression. Phase-steered arrays offer angular control but lack range-dependent response, preventing true two-dimensional focusing. Frequency-Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) architectures introduce element-wise frequency offsets to enrich spatial–spectral degrees of freedom, yet conventional linear or predetermined nonlinear offsets cause range–angle coupling, periodic lobes, and restricted beamforming flexibility. Existing optimization strategies also tend to target single objectives and insufficiently address target- or scene-induced perturbations. This work proposes a nonlinear frequency-offset design for passive microwave arrays using a Dingo–Gray Wolf hybrid intelligent optimizer. A multi-metric fitness function simultaneously enforces sidelobe suppression, null shaping, and frequency-offset smoothness. Simulations in static scenarios show that the method achieves high-resolution two-dimensional focusing, enhanced interference suppression, and stable performance under realistic spatial–spectral mismatches. The results demonstrate an effective approach for improving the controllability and robustness of passive microwave array components on static platforms. Full article

E-scooters have rapidly become a popular option for first- and last-mile mobility, yet their integration into urban transportation systems has raised significant safety concerns. This study investigates the feasibility of permitting E-scooter riding on sidewalks under controlled conditions to minimize pedestrian conflicts. Analysis of E-scooter crashes in Daejeon, South Korea, showed that 98.09% of crashes were caused by rider negligence, with “Failure to Fulfill Safe Driving Duty” as the leading factor. To investigate the applicability of safe sidewalk usage, a VR-based simulator experiment was conducted with 41 participants across four scenarios with varying sidewalk widths and pedestrian densities, under speed limits of 10, 15, and 20 km/h. Riding behaviors—including speed stability, braking, steering, and conflict frequency—and gaze behaviors were measured. Results showed that riding at 10 km/h improved riding stability and minimized conflicts. Regression analysis identified pedestrian density as the strongest predictor of conflicts, followed by sidewalk width and riding speed. These findings suggest specific policy needs: ensuring a minimum sidewalk width of 4 m for safe shared use, restricting operation to environments with low-to-moderate pedestrian density, and implementing a 10 km/h speed limit. This study provides evidence-based recommendations for safer integration of E-scooters into pedestrian environments. Full article

Crawler-type combine harvesters feature labor-intensive operation, tough steering and complex environments in paddy fields, necessitating reliable automatic operation to ensure efficient and complete harvesting. An error threshold-based autonomous navigation system for crawler-type combine harvesters was developed by using right-angle turning according to unilateral brake steering. Based on the chassis structure and working principles, a moving control system was designed to achieve automatic control of steering, speed and throttle. A global path planning method was proposed to generate a spiral path by giving reference points and operation directions. A path tracking method based on the error threshold was developed to calculate both lateral and heading errors in real-time, and we executed the adjustment strategy to ensure rapid alignment and high-precision tracking. A right-angle turning method was implemented to prevent missed cutting and crop damage by giving an adjustment distance. Field tests showed that the maximum lateral and heading errors for straight-line path tracking were 10.25 cm and 1.94°, respectively. The maximum lateral and heading errors for right-angle turning were 17.64 cm and −14.46°, respectively. It was concluded that the newly developed autonomous navigation system showed adequate path tracking accuracy and stability, meeting working requirements in crop harvesting. Full article