Search Results (2,823)

The electrification of vehicle chassis systems is increasingly important due to benefits such as vehicle lightweighting, enhanced safety, and design flexibility. However, faults in these systems can seriously compromise safety, making Fault Tolerant Control (FTC) essential. This study investigated FTC of four-wheel independent Electro-Mechanical Brake (EMB) actuators and proposed a method to prevent lane departure under actuator faults. Fault Tolerant Robust Control (FTRC) of four-wheel independent EMB actuators using Time Delay Control (TDC) was applied without Fault Detection and Diagnosis (FDD) to maintain real-time capability, and without steering control to reduce system complexity. In addition, for actuator faults causing large lateral displacements, a control strategy applying relative weighting to lateral velocity and yaw rate was introduced. The results showed that, even when the faults of the EMB actuators were severe and asymmetric between the left and right sides of the vehicle, overall vehicle stability—including lateral and yaw motions—was preserved through the proposed FTRC approach without FDD and steering control. Moreover, the relative weighting strategy effectively reduced lateral displacement, preventing lane departure. These findings highlight the significance of the proposed method for ensuring FTRC in electrified braking systems, enhancing safety, reducing lateral displacement, preventing lane departure, ensuring real-time capability, and reducing the complexity required in practical FTC. Full article

Background/Objectives: Cruciate-retaining (CR) and posterior-stabilized (PS) total knee arthroplasty (TKA) are both widely used in primary knee osteoarthritis (KOA), but evidence in younger patients remains limited. This study compared functional outcomes, pain, range of motion, quality of life, and psychological status between CR and PS implants in an Eastern European cohort. Methods: A prospective comparative cohort study was conducted in patients aged 40–64 years undergoing primary cemented TKA. The primary outcome was change in the Lower-Extremity Functional Scale (LEFS) at 12 months. Secondary outcomes included the Lysholm Knee Scoring Scale, EQ5D5L index, visual analogue scale (VAS) for pain, PROMIS Depression score, active knee flexion, and patient satisfaction. Outcomes were evaluated at baseline, 6 weeks, 3 months, 6 months, and 12 months. Between-group comparisons used Welch t-tests and results are reported as mean differences with 95% confidence intervals. Results: A total of 147 patients were included (CR n = 71; PS n = 76). The prespecified primary endpoint, 12-month change in LEFS, was very similar between groups (mean difference 0.14 points, 95% CI −3.80 to 4.08; p = 0.94). LEFS improved from 49.1 ± 14.8 to 66.8 ± 11.6 in the CR group and from 47.9 ± 14.6 to 65.8 ± 12.4 in the PS group at 12 months. Lysholm scores increased to 88.5 ± 11.4 (CR) and 86.2 ± 10.6 (PS) (p = 0.21). EQ-5D-5L improved in both groups, with a non-significant difference at 12 months (p = 0.077). VAS pain decreased from 7.39 ± 1.19 to 1.59 ± 0.84 (CR) and from 7.55 ± 1.46 to 1.75 ± 0.90 (PS) (p = 0.27). Active flexion increased to 117.5 ± 10.5° (CR) and 115.0 ± 11.3° (PS) (p = 0.15). PROMIS Depression improved similarly in both groups, and satisfaction levels at 12 months were comparable. Conclusions: Both CR and PS TKA produced comparable improvements in pain, function, quality of life, mental health, and knee flexion in KOA patients aged 40–64 at one year. Implant design did not influence clinical benefit or PROMs in this cohort. Full article

Humanoid robots have gained public awareness and intrigue over the last few years. During this time, there has been a greater push to develop robots to behave more like humans, not just in how they speak but also in how they move. A novel humanoid robotic head-and-neck platform designed to facilitate the investigation of movement characteristics is proposed. The research presented here aims to characterise the motion of a humanoid robotic head, Aquila, to aid the development of humanoid robots with head movements more similar to those of humans. This platform also aims to promote further studies in human head motion. This paper proposes a design for a humanoid robotic head platform capable of performing three principal human motion patterns: yaw, pitch, and roll. Using the Arduino IDE (2.3.2) and MATLAB/Simulink (2024b), all three types of movement were implemented and tested with various parameters. Each type of movement is quantified in terms of range, stability, and dynamic response using time-series data collected over 35 s of continuous observation. The results demonstrate that a humanoid robot head can mimic the range of displacement of a healthy human subject but does not exhibit the same smoothness and micro-adjustments observed in dynamic human head movements. An RMSE of under 0.3 rad is achieved for each motion axis—pitch, roll, and yaw—when comparing robotic head movement to human head movement. The investigation of preliminary results highlights the need for further system optimisation. This paper’s conclusion highlights that the bio-inspired control concept, paired with the proposed 8-stepper motor platform, enhances realism and interaction in the context of head movement in robotic systems. Full article

To address the issue of limited accuracy in vehicle lateral and longitudinal dynamics control—caused by the strong coupling and nonlinearity between the four-wheel steering and distributed drive systems, particularly under crosswind disturbances—a control method integrating differential geometric decoupling with robust control is proposed. This integrated approach mitigates coupling effects among the vehicle motions in various directions, thereby enhancing overall robustness. The control architecture adopts a hierarchical structure: the upper layer takes the deviation between the ideal and actual models as input and generates longitudinal, yaw, and lateral control laws via robust control; the middle layer employs differential geometric methods to decouple the nonlinear system, deriving the total driver-required driving torque, additional yaw moment, and rear-wheel steering angle; and the lower layer utilizes a quadratic programming algorithm to optimize the distribution of driving torque across the four wheels. Finally, simulation verification is conducted based on a co-simulation platform using TruckSim 2022 and MATLAB R2024a/Simulink. The simulation results demonstrate that, compared to the sliding mode control (SMC) and the uncontrolled scenario, the proposed method improves the driving stability and safety of the four-wheel steering distributed drive vehicle under multiple operating conditions. Full article

The maneuverability of a submarine in the vertical plane is a key indicator of navigation safety. However, existing studies typically evaluate maneuvering performance based on hydrodynamic coefficients, often neglecting the flow-field evolution induced by different steering strategies. In this study, a high-fidelity numerical model for the vertical-plane motion of the DARPA SUBOFF submarine is established using the Reynolds-Averaged Navier–Stokes (RANS) method and validated against benchmark data. Unlike traditional analyses that employ a fixed rudder angle, this work systematically compares three steering strategies with continuously varying rudder angles—trapezoidal, step, and linear steering—examining their motion responses, hydrodynamic performance, and unsteady flow-field evolution. The results show that, although step steering produces the fastest response with the strongest transient characteristics, it also triggers pronounced flow separation and significant unsteady effects. Linear steering yields a smoother but the weakest motion response, with reduced rudder effectiveness and a noticeable lag effect. In contrast, trapezoidal steering maintains a stable flow field around the submarine, with uniformly concentrated vorticity distribution, ensuring smooth and safe motion and achieving a favorable balance between response speed and flow stability. The findings provide theoretical reference for research on submarine vertical-plane steering motion, rudder-angle control, and flow-field stability. Full article

(1) Background: The midsole hardness (i.e., cushioning) of running shoes has received significant attention as a crucial element influencing both performance and injury prevention. This research aimed to examine how variations in midsole hardness affect the biomechanical responses of the lower extremities during running. (2) Methods: Twenty-five male recreational runners in their 20 s with no history of musculoskeletal injuries (age: 23.3 ± 4.24 years) were recruited. Custom-made shoes with four different midsole hardness levels (Asker-C 70, 60, 50, and 40) were used, and the mechanical properties of the midsoles were analyzed. Participants ran on an instrumented treadmill at speeds of 2.3 m/s and 3.3 m/s. Ground reaction forces and motion data were collected during the trials. A one-way repeated-measures ANOVA was conducted to compare groups. (3) Results: In the running trials, a decrease in midsole hardness increased the impact peak (IP) while loading rate (LR) decreased significantly (p < 0.05). In addition, runners wearing shoes with greater cushioning exhibited higher ankle joint stiffness than those wearing harder shoes (p < 0.05). (4) Conclusions: Adjusting joint stiffness appears to be a key strategy employed by runners in response to softer or cushioned running environments (i.e., shoe and surface), ultimately contributing to greater dynamic stability during movement. Full article

Accurately reproducing the mechanical and dynamic behavior of fractured rock masses remains a key challenge in rock engineering, especially in marble quarry environments where discontinuity networks, excavation geometry, and topographic effects induce highly non-linear stress distributions. This study presents a multidisciplinary and physically calibrated numerical approach integrating field stress measurements, structural characterization, and dynamic modeling using the Distinct Element Method (DEM). The analysis focuses on a marble quarry located in the Apuan Alps (Italy), a tectonically complex metamorphic massif characterized by intense deformation and pervasive jointing that strongly influence rock mass behavior under both static and seismic loading. The initial stress field was calibrated using in situ measurements obtained by the CSIRO Hollow Inclusion technique, enabling reconstruction of the three-dimensional principal stress regime and its direct incorporation into a 3DEC numerical model. The calibrated model was then employed to simulate the dynamic response of the rock mass under seismic loading consistent with the Italian Building Code (NTC 2018). This coupled static–dynamic workflow provides a realistic evaluation of ground motion amplification, stress concentration, and potential failure mechanisms along pre-existing discontinuities. Results demonstrate that physically validated stress initialization yields a significantly more realistic response than models based on simplified lithostatic or empirical assumptions. The approach highlights the value of integrating geological, geotechnical, and seismological data into a unified modeling framework for a sustainable quarry stability analysis in fractured rock masses. Full article

Video-centric applications have seen significant growth in recent years with HTTP Adaptive Streaming (HAS) becoming a widely adopted method for video delivery. Recently, low-latency (LL) adaptive bitrate (ABR) algorithms have recently been proposed to reduce the end-to-end delay in HTTP adaptive streaming. This study investigates whether low-latency adaptive bitrate (LL-ABR) algorithms, in their effort to reduce delay, also compromise video quality. To this end, this study presents both objective and subjective evaluation of user experience with traditional DASH and low-latency ABR algorithms. The study employs crowdsourcing to evaluate user-perceived video quality in low-latency MPEG-DASH streaming, with a particular focus on the impact of short segment durations. We also investigate the extent to which quantitative QoE (Quality of Experience) metrics correspond to the subjective evaluation results. Results show that the Dynamic algorithm outperforms the low-latency algorithms, achieving higher stability and perceptual quality. Among low-latency methods, Low-on-Latency (LOL+) demonstrates superior QoE compared to Learn2Adapt-LowLatency (L2A-LL), which tends to sacrifice visual consistency for latency gains. The findings emphasize the importance of integrating subjective evaluation into the design of ABR algorithms and highlight the need for user-centric and perceptually aware optimization strategies in low-latency streaming systems. Our results show that the subjective scores do not always align with objective performance metrics. The viewers are found to be sensitive to complex or high-motion content, where maintaining a consistent user experience becomes challenging despite favorable objective performance metrics. Full article

Underwater Vehicle-Manipulator Systems (UVMSs) play a critical role in various marine operations, where the choice of manipulator architecture significantly influences system performance. While serial robotic arms have been widely adopted in UVMS applications due to their operational flexibility, their inherent structural characteristics present certain challenges in underwater environments. These challenges primarily stem from the cumulative effects of joint mechanisms and dynamic interactions with the fluid medium. In this context, we explore an innovative UVMS solution that incorporates the Delta parallel mechanism, which offers distinct advantages through its symmetrical architecture and unilateral motor configuration, particularly in maintaining operational stability. We develop a comprehensive framework that includes mechanical design optimization, implementation of distributed control systems, and formulation of closed-form kinematic models, with comparative analysis against conventional serial robotic arms. Experimental validation demonstrates the system’s effectiveness in underwater navigation, target acquisition, and object manipulation under operator-guided control. The results reveal substantial enhancements in motion consistency and gravitational stability compared to traditional serial-arm configurations, positioning the Delta-based UVMS as a viable solution for complex underwater manipulation tasks. Furthermore, this study provides a comparative analysis of the proposed Delta-based UVMS and conventional serial-arm systems, offering valuable design insights and performance benchmarks to inform future development and optimization of underwater manipulation technologies. Full article

Unmanned underwater vehicles (UUVs) face significant challenges in achieving safe and efficient autonomous navigation in complex marine environments due to uncertain perception, dynamic obstacles, and nonlinear coupled motion control. This study proposes a hierarchical autonomous navigation framework that integrates improved particle swarm optimization (PSO) for 3D global route planning, and a deep deterministic policy gradient (DDPG) algorithm enhanced by noisy networks and proportional prioritized experience replay (PPER) for local collision avoidance. To address dynamic sideslip and current-induced deviations during execution, a novel 3D adaptive line-of-sight (ALOS) guidance method is developed, which decouples nonlinear motion in horizontal and vertical planes and ensures robust tracking. The global planner incorporates a multi-objective cost function that considers yaw and pitch adjustments, while the improved PSO employs nonlinearly synchronized adaptive weights to enhance convergence and avoid local minima. For local avoidance, the proposed DDPG framework incorporates a memory-enhanced state–action representation, GRU-based temporal processing, and stratified sample replay to enhance learning stability and exploration. Simulation results indicate that the proposed method reduces route length by 5.96% and planning time by 82.9% compared to baseline algorithms in dynamic scenarios, it achieves an up to 11% higher success rate and 10% better efficiency than SAC and standard DDPG. The 3D ALOS controller outperforms existing guidance strategies under time-varying currents, ensuring smoother tracking and reduced actuator effort. Full article

This paper presents a new approach to the dimensional synthesis of a robotic limb mechanism for a wheel-legged robot. The proposed kinematic structure enables independent control of wheel motions relative to the robot platform, allowing each drive to perform a distinct movement. The selection of the mechanism’s common dimensions simplifies platform levelling to a single-drive actuation. The hybrid limb design, which combines features of driving and walking systems, enhances platform stability on uneven terrain and is suitable for rescue, exploration, and inspection robots. The synthesis method defines the desired trajectory of the wheel centre and applies a genetic algorithm to determine mechanism dimensions that reproduce this motion. The stochastic optimisation process yields multiple feasible solutions, enabling the introduction of additional design criteria for optimal configuration selection. Analytical kinematic relations were developed for workspace and trajectory evaluation, solving both direct and inverse kinematic problems. The results confirm the effectiveness of evolutionary optimisation in synthesising complex kinematic mechanisms. The proposed approach can be adapted to other mobile robot structures. Future work will address dynamic modelling, adaptive control for real-time platform levelling, and comparative studies with other synthesis methods. Full article

This paper presents OcclusionTrack (OCCTrack), a robust multi-object tracker designed to address occlusion challenges in dense scenes. Occlusion remains a critical issue in multi-object tracking; despite significant advancements in current tracking methods, dense scenes and frequent occlusions continue to pose formidable challenges for existing tracking-by-detection trackers. Therefore, four key improvements are integrated into a tracking-by-detection paradigm: (1) a confidence-based Kalman filter (CBKF) that dynamically adapts measurement noise to handle partial occlusions; (2) camera motion compensation (CMC) for inter-frame alignment to stabilize predictions; (3) a depth–cascade-matching (DCM) algorithm that uses relative depth to resolve association ambiguities among overlapping objects; and (4) a CMC-detection-based trajectory Re-activate method to recover and correct tracks after complete occlusion. Despite relying solely on IoU matching, OCCTrack achieves highly competitive performance on MOT17 (HOTA 64.9, MOTA 80.9, IDF1 79.7), MOT20 (HOTA 63.2, MOTA 76.9, IDF1 77.5), and DanceTrack (HOTA 57.5, MOTA 91.4, IDF1 58.4). The primary contribution of this work lies in the cohesive integration of these modules into a unified, real-time pipeline that systematically mitigates both partial and complete occlusion effects, offering a practical and reproducible framework for complex real-world tracking scenarios. Full article

Marine risers, critical structures connecting underwater production systems and surface floating platforms, stand freely in water and endure extremely complex marine environmental loads. To meet the multi-parameter observation demand for their overall state, a fiber-optic sensing-based marine riser buoy observation system was developed. Unlike traditional point-type and offline monitoring systems, it integrates marine buoys with sensing submarine cables to achieve long-term real-time online monitoring of risers’ overall state via fiber-optic sensing technology. Comprising two main modules (buoy monitoring module and fiber-optic sensing module), the buoy’s stability was verified through theoretical derivation, simulation, and stability curve plotting. Frequency domain analysis of buoy loads and motion responses, along with calculation of motion response amplitude operators (RAOs) at various incident angles, showed the system avoids wave periods in the South China Sea (no resonance), ensuring structural safety for offshore operations. A 7-day marine test of the prototype was conducted in Yazhou Bay, Hainan Province, to monitor real-time temperature and strain data of the riser in the test sea area. The sensing submarine cable accurately responded to temperature changes at different depths with high stability and precision; using the Frenet-based 3D curve reconstruction algorithm, pipeline shape was inverted from the monitored strain data, enabling real-time pipeline monitoring. During the test, the buoy and fiber-optic sensing module operated stably. This marine test confirms the buoy observation system’s reasonable design parameters and feasible scheme, applicable to temperature and deformation monitoring of marine risers. Full article

Maintaining lower-limb joint stability is essential for safe and efficient performance during landing and directional changes. This pilot study examined the effects of a 10-week perturbation-based Dynamic Stability Training (DST) program using an inertial water load on lower-limb joint moments during single-leg landing and a 3-s stabilization phase following a 90° cutting maneuver. Fifteen healthy young men completed DST twice weekly. Three-dimensional motion capture and force-plate data were collected at pre-, mid-, and post-training to compute hip, knee, and ankle joint moments. During landing, hip flexion and abduction moments increased, whereas knee abduction moment decreased. During the stabilization phase, hip flexion, hip rotation, and ankle abduction moments decreased, while knee abduction moment increased. These joint-specific changes suggest potential adaptations in frontal- and transverse-plane control when training with unstable inertial water loads; however, interpretations should remain cautious given the exploratory design and absence of a control group. Larger randomized controlled trials are needed to confirm these preliminary findings. Full article

Human–robot cooperative tasks require physical human–robot interaction (pHRI) systems that can adapt to individual human behaviors while ensuring robustness and stability. This paper presents a dual-loop control framework combining an admittance outer loop and a neural adaptive inner loop based on the Robust Integral of the Sign of the Error (RISE) approach. The outer loop reshapes the manipulator trajectory according to interaction forces, ensuring compliant motion and user safety. The inner-loop Adaptive RISE–RBFNN controller compensates for unknown nonlinear dynamics and bounded disturbances through online neural learning and robust sign-based correction, guaranteeing semi-global asymptotic convergence. Quantitative results demonstrate that the proposed adaptive RISE controller with neural-network error compensation (ARINNSE) achieves superior performance in the Joint-1 tracking task, reducing the root-mean-square tracking error by approximately 51.7% and 42.3% compared to conventional sliding mode control and standard RISE methods, respectively, while attaining the smallest maximum absolute error and maintaining control energy consumption comparable to that of RISE. Under human–robot interaction scenarios, the controller preserves stable, bounded control inputs and rapid error convergence even under time-varying disturbances. These results confirm that the proposed admittance-based RISE–RBFNN framework provides enhanced robustness, adaptability, and compliance, making it a promising approach for safe and efficient human–robot collaboration. Full article