Search Results (149)

Non-invasive, real-time biomass estimation is critical for smart aquaculture, yet high computational latency and the cost of specialized optical sensors remain significant bottlenecks. This study proposes an ultra-low-cost, edge-deployable stereo-vision framework utilizing a dual-webcam architecture synchronized with a lightweight YOLOv11n-pose model. To address the spatial uncertainties in non-rigid fish locomotion, we integrated advanced spatial loss functions to achieve precise anatomical keypoint extraction. These coordinates are processed through a three-point Bézier curve interpolation and a mathematically derived Dynamic Shape Factor (K) to correct for optical refraction and morphological variations. As a proof-of-concept, the proposed system was validated on a live multi-species cohort (N = 10), achieving a Mean Absolute Percentage Error (MAPE) of 8.64% and an R² of 0.92 under strict Leave-One-Out Cross-Validation (LOOCV), drastically outperforming traditional naive volumetric baselines (MAPE > 54%). Requiring only 6.7 GFLOPs and 5.5 MB of memory, the model achieves 111.6 FPS. These results demonstrate the feasibility of highly efficient, cost-effective AI solutions for precision aquaculture while clearly defining the validity boundaries and statistical constraints for future large-scale deployment. Full article

In-pipe robots must navigate narrow, curved passages where rigid mechanisms often require bulky steering units. Soft crawlers offer better compliance but typically rely on multiple actuators or reconfigurable contacts to achieve multi-directional motion. Drawing inspiration from biological soft crawlers that exploit directional friction and coordinated anchor–slip patterns, this study focuses on locomotion principles observed in caterpillars, water boatmen, and whirligig beetles. Based on these bioinspired concepts, we present a tendon-driven soft in-pipe robot that combines continuum bending–twisting deformation with modular anisotropic friction pads (AFPs), enabling three locomotion modes using only two motors. AFP inclination, curvature, and ridge geometry were optimized through friction tests, constant-curvature modeling, and finite element analysis to enhance directional adhesion on flat and curved surfaces. A deformation-based locomotion framework was developed to couple tendon actuation with friction orientation, achieving longitudinal crawling, transverse translation, in-place rotation, and smooth transitions via programmed twisting. Driving experiments demonstrated repeatable anchor–slip locomotion with average speeds of 28.6 mm/s, 15.7 mm/s, and 11.5°/s for the three modes. Pipe tests in straight, curved, and T-junction sections further validated stable contact and reliable gait transitions. These findings highlight the potential of friction-programmed continuum robots as compact, bioinspired platforms for advanced in-pipe inspection and diagnostic tasks. Full article

To investigate the influence of train operating speed on the transient characteristics of the pantograph–catenary arc, this paper establishes an integrated simulation model encompassing the traction network, electric locomotive, and arc. In this model, the traction network adopts a chain circuit model based on multi-conductor transmission line theory. The electric locomotive model considers the train body and the on-board transformer. For the pantograph–catenary offline arc, an improved Habedank model is employed, which takes the train operating speed and arc current as variables. Based on this model, this paper systematically investigates the variation patterns of arc electrical parameters and transient currents in each line of the traction network with train operating speed under pantograph–catenary offline. The simulation results indicate that as train speed increases, both the steady-state arc voltage and the maximum voltage at arc ignition rise, and the arc extinction time at current zero-crossing is prolonged. The peak arc currents on the contact wire, feeder, protective wire, and rails decrease, while the transient current on the ground wire increases. This study can provide a reference for the electromagnetic compatibility design, insulation coordination optimization, and electromagnetic protection of high-speed railway traction power supply systems. Full article

Bio-inspired quadrupedal robots exhibit superior adaptability and mobility in unstructured environments, making them suitable for complex task scenarios such as navigation, obstacle avoidance, and tracking in a variety of environments. Visual perception plays a critical role in enabling autonomous behavior, offering a cost-effective alternative to multi-sensor systems. This paper proposes an image segmentation-guided visual tracking framework to enhance both perception and motion control in quadruped robots. On the perception side, a cascaded convolutional neural network is introduced, integrating a global information guidance module to fuse low-level textures and high-level semantic features. This architecture effectively addresses limitations in single-scale feature extraction and improves segmentation accuracy under visually degraded conditions. On the control side, segmentation outputs are embedded into a biologically inspired central pattern generator (CPG), enabling coordinated generation of limb and spinal trajectories. This integration facilitates a closed-loop visual-motor system that adapts dynamically to environmental changes. Experimental evaluations on benchmark image segmentation datasets and robotic locomotion tasks demonstrate that the proposed framework achieves enhanced segmentation precision and motion flexibility, outperforming existing methods. The results highlight the effectiveness of vision-guided control strategies and their potential for deployment in real-time robotic navigation. Full article

Background/Objectives: Freezing of gait (FoG) is a disabling motor manifestation of Parkinson’s disease (PD) associated with impaired neural control of locomotion and increased gait variability. Quantitative characterization of gait kinematics may provide biomechanical insight into FoG-related instability, particularly under different dopaminergic states. Methods: This pilot study evaluated sagittal-plane knee kinematics in healthy individuals (n = 27) and patients with PD. (n = 8) under OFF and ON dopaminergic medication conditions using two-dimensional videogrammetry (Kinovea^®). Knee flexion–extension trajectories were time-normalized to 0–100% of the gait cycle, and group ensemble profiles (mean ± SD) were computed. Results: Phase-specific range of motion (ROM), within-subject variability, and interlimb coordination were quantified. Interlimb coordination was assessed using Pearson’s correlation coefficients (r) and cross-correlation lag analysis computed per subject and summarized statistically across groups. Compared with healthy participants, PD patients in the OFF state exhibited significantly reduced knee ROM during stance and swing (p < 0.05), accompanied by increased kinematic variability and disrupted temporal coordination. Interlimb correlation was significantly lower in PD OFF compared to healthy gait groups (p = 0.010), with larger temporal lags, indicating impaired bilateral synchronization. Following medication intake (ON state), knee excursion increased and interlimb coordination partially improved; however, correlation values and timing symmetry did not fully normalize to healthy levels. Conclusions: These findings demonstrate that sagittal-plane knee kinematics and interlimb coordination metrics derived from low-cost 2D videogrammetry are sensitive to the dopaminergic state and reveal persistent neuromotor deficits in PD. The proposed framework provides an interpretable and accessible approach for characterizing gait organization in Parkinson’s disease and supports future integration with clinical assessment and longitudinal monitoring. Full article

Background: Joubert syndrome (JS) is a rare ciliopathy characterized by cerebellar and brainstem malformations and the molar tooth sign on magnetic resonance imaging. Motor impairment is primarily driven by axial hypotonia, impaired postural control, and disrupted respiratory-postural integration. Longitudinal reports describing structured neurorehabilitation with standardized functional outcomes remain limited. Case presentation: We report a female child with prenatally suspected vermian hypoplasia and postnatally MRI-confirmed Joubert syndrome. Subsequent molecular testing performed at the age of 3 years and 11 months identified heterozygous variants in the B9D2 gene associated with Joubert syndrome. Early development was marked by axial hypotonia, global motor delay, impaired trunk stabilization, sleep-disordered breathing, and early hip migration. At 2.5 years of age, following motor plateau under conventional therapy, a structured 12-month rehabilitation programme was introduced, combining Vojta-based reflex locomotion, respiratory therapy targeting thoraco-diaphragmatic synchronization, daily home-based practice, and supported standing. Results: After 12 months, gross motor function improved substantially, with GMFM-88 increasing from 12% to 52% (+40 percentage points). PEDI scaled scores improved across all domains, with mobility increasing from 8 to 40, self-care from 15 to 45, and social function from 25 to 50. Ataxia severity decreased from 22 to 15 on the modified Brief Ataxia Rating Scale, consistent with improved trunk stability and coordination. Postural and respiratory organization improved, reflected by a reduction in the subcostal angle from 137° to 90°, an increase in sacral slope from 5° to 10°, and increased expiratory pressure from 10 to 25 mmHg. Caregiver-reported assessment combined with structured clinical observation indicated improved functional visual performance, including enhanced visual attention, visuomotor coordination, and environmental visual interaction. Conclusions: Structured neurorehabilitation was associated with substantial functional improvement across motor, postural, and respiratory domains. These findings support the clinical relevance of mechanism-oriented neurorehabilitation and standardized longitudinal outcome assessment in Joubert syndrome. Full article

This paper studies a MuJoCo-based locomotion framework that couples an adaptive-frequency central pattern generator (AFCO-CPG) with single rigid-body dynamics model predictive control (MPC) for the RENS Q1 quadruped with elastic parallel knee joints. AFCO-CPG combines multi-scale phase coordination, saturated phase correction, and load-gated feedback, while MPC supplies feasible ground-reaction forces and returns load cues to the timing layer. In MuJoCo, the controller achieves stable diagonal-trot speed tracking from 0.4 to 1.2 m/s and recovers from short external pushes. A matched elastic-versus-rigid timing sweep shows a favorable flat-ground parameter band around $\omega =1.8$ Hz, with a best-case cost-of-transport reduction of 12.83% for the elastic model under identical controller gains. A flat-to-slope ascent case further verifies that AFCO timing is modulated when load conditions change. Ablation across nine controller variants shows that multi-scale coordination is the dominant component, causing a 135% increase in phase error and a 536% increase in recovery time when removed. A reduced-order early/late-contact benchmark further confirms faster re-locking than diagonal-only and minimal variants. The results support the value of combining neural timing, predictive force optimization, and compliant-leg feedback in high-fidelity simulation, while hardware validation remains future work. Full article

Biarticular actuators can enhance efficiency and stability in legged locomotion by transferring energy between joints. Their effectiveness depends strongly on the lever arm ratio—the ratio of the actuator’s moment arm at one joint to its moment arm at another—which governs how torque is distributed across joints during movement. Inspired by biomechanics, early robotic studies implemented biarticular actuators to improve energy efficiency, joint coordination, and positional control, primarily in planar or single-joint systems, leaving a gap in fully 3D robotic legs. Here, we present a geometry optimization framework for a robotic leg incorporating both biarticular and monoarticular actuators. Using human motion capture and joint torque data, we optimized the linkage mechanisms so that the system can maintain the required joint torques while keeping biarticular actuator moment arm ratios near their optimal values during walking and running. The optimized leg achieved a minimum achievable cost of transport of approximately $0.41 \mathrm{J}/(\mathrm{kg}·\mathrm{m})$ for walking and $0.62 \mathrm{J}/(\mathrm{kg}·\mathrm{m})$ for running. Full article

This paper presents the design and experimental evaluation of a bio-inspired gecko robot, focusing on mechanical design, vision-based obstacle perception, and rhythmic locomotion control as enabling technologies for future obstacle avoidance in complex environments. The robot features a 17-degrees-of-freedom mechanical structure with a flexible spine and multi-jointed limbs, providing a physical basis for adaptive locomotion. For perception, a custom obstacle detection dataset was constructed from the robot’s onboard camera view and used to train a YOLOv5-based detection model. Experimental results show that the trained model achieves a mean average precision (mAP) of 0.979 and a maximum F1-score of 0.97 at an optimal confidence threshold, demonstrating reliable real-time obstacle perception under diverse indoor conditions. For motion control, a central pattern generator (CPG) based on Hopf oscillators is implemented to generate rhythmic locomotion. Experimental evaluations confirm stable diagonal gait generation, with coordinated joint trajectories oscillating at 1 Hz. The flexible spine exhibits periodic lateral deflection with peak amplitudes of ±15°, ±10°, and ±8° across spinal joints, enhancing locomotion continuity and turning capability. Physical robot experiments further demonstrate smooth straight-line crawling enabled by the coupled limb–spine motion. While visual perception and CPG-based locomotion are experimentally validated as independent subsystems, their real-time closed-loop integration is not implemented in this study. Instead, this work establishes a system-level framework and experimental baseline for future perception–motion coupling, providing a foundation for closed-loop obstacle avoidance and autonomous navigation in bio-inspired gecko robots. Full article

Bipedal wheeled robots combine the advantages of wheeled mobility and legged agility, enabling high-speed locomotion and obstacle negotiation in complex environments. However, their dynamic behavior is inherently unstable and highly coupled, making robust control particularly challenging in the presence of task conflicts, external disturbances, and modeling uncertainties. This paper proposes an RBF–L1–WBC framework that integrates L1 adaptive control to compensate for model inaccuracies and disturbances, radial basis function (RBF) neural networks to approximate nonlinear variations in linear quadratic regulator (LQR) gains, and whole-body control (WBC) to coordinate multiple tasks while mitigating control conflicts. Experimental findings confirm that the proposed methodology yields statistically significant improvements in both attitude regulation precision and velocity tracking accuracy, surpassing the performance of benchmark controllers including classical LQR, adaptive LQR, and classical Virtual Model Control (VMC). Full article

Exploring the lunar complex and extreme terrain presents formidable challenges for conventional lunar rovers. To address these limitations, this study proposes a novel hexapod jumping hybrid robot that incorporates a “figure-of-eight” (butterfly-shaped) six-branched wheel-legged mechanism and a jumping system that stores elastic energy via deformation of its elastic body. Inspired by the multimodal locomotion of grasshoppers, the robot dynamically switches between two operational modes: high-efficiency wheeled locomotion on relatively flat surfaces and agile jumping to traverse steep slopes and surmount large obstacles. A bio-inspired gait, inspired by the crawling patterns of a hexapod insect, is implemented using a Central Pattern Generator (CPG)-based controller to produce coordinated, rhythmic limb movements. Dynamic simulations of the jumping mechanism were conducted to optimize the critical parameters of the elastic structure and its associated control strategy. Experiments on a physical prototype were conducted to validate the robot’s wheeled mobility and jumping performance. The results demonstrate that the robot exhibits excellent adaptability to rugged terrains and obstacle-dense environments. The integration of multimodal locomotion and adaptive gait control significantly enhances the robot’s operational robustness and survivability in the harsh lunar environment, opening new possibilities for future lunar exploration missions. Full article

Myriapods achieve remarkable obstacle-crossing capability through inter-segment pitch adjustment and coordinated anterior–posterior propulsion, providing valuable biomimetic inspiration for engineering design. Articulated tracked vehicles, connecting front and rear units via pitch mechanisms, exhibit functional similarity to myriapod body segments. This study develops a comprehensive dynamic model for articulated tracked vehicle pitch motion to reveal its biomimetic connection with myriapod locomotion. A quadratic-function-based non-uniform track–ground contact pressure distribution method with zero-gradient boundary conditions is proposed, effectively eliminating the non-physical negative pressure issue inherent in traditional assumptions. Systematic analyses reveal that the front unit provides primary traction under pitch-up conditions, forming a front-pulling-rear driving mode, while the rear unit dominates under pitch-down and acceleration conditions, forming a rear-pushing-front driving mode. Through pitch attitude adjustment, the maximum surmountable vertical-wall height increased from 263 to 593 mm, representing a 125.45% improvement. This traction distribution pattern closely matches the anterior-guidance and posterior-propulsion mechanism observed in myriapod locomotion. This study quantitatively validates the functional analogy between articulated tracked vehicle pitch dynamics and myriapod inter-segment coordination, providing theoretical foundations for bio-inspired tracked vehicle design. Full article

In recent decades, robotic locomotion has applied different techniques to emulate central pattern generators (CPGs). The theory of CPG explains the biological functions of motor control in living organisms. This paper presents an unpublished model for coupled nonlinear oscillators. This model employs a canonical nonlinear differential equation system to coordinate joint activity. The analysis, conducted under the criteria of chaos and bifurcation theory, determines that the new model is successful and without the presence of chaos. The new model is compared with other cases, including the Wilson–Cowan, Hopf, and Van Der Pol models, as well as with the operability of different robots. It highlights the new model’s advantages in terms of versatility, simplicity, and processing, as well as the comparisons of metrics of locomotion, such as support factor and symmetry index between hemibody metrics. The new model is applied to the locomotion of two quadruped robots (a crab and a dog) used in research on transitions between types of locomotion, considering both physical and computational limitations. Full article

Adaptive locomotion requires the integration of cognitive and motor processes and is challenged in neurological disorders. Dual-task (DT) training may improve cognitive–motor coordination, but its feasibility across heterogeneous clinical populations is uncertain. This pilot study aimed to understand if the effects of a secondary motor or cognitive task added to a walking task depend on the functional walking abilities of the subjects. We enrolled 30 participants with neurological disorders not related to traumatic events, 5 for each one of the following groups: healthy young subjects (HeY), healthy control subjects (HeC), subjects with stroke (ictus, IC), Parkinson’s disease (PD), multiple sclerosis (MS), and Long-COVID sequelae (LC). Spatiotemporal gait parameters were recorded using a wearable inertial magnetic unit, and subjective workload was assessed with the visual analog scale (VAS) and NASA-Task Load Index. Regression models revealed strong baseline–DT coupling for stride duration (slopes 1.11–1.37; R² 0.85–0.97), stride length (slopes 0.93–0.94; R² 0.86–0.93), walking speed (slopes 0.87–0.98; R² 0.78–0.93), and gait ratio (stance/swing, slopes 0.38–0.60; R² 0.21–0.52). Mixed-effects analyses identified significant group effects for walking speed (F(5) = 7.218, p < 0.001), stride length (F(5) = 4.834, p = 0.001), gait cycle duration (F(5) = 5.630–5.664, p < 0.001), Walking Quality (F(5) = 4.340–4.373, p = 0.001), and propulsion index (F(5) = 5.668–6.843, p < 0.001). The incongruent DT condition was the most sensitive in differentiating clinical groups. NASA-TLX indicated higher perceived workload in IC and MS compared with non-clinical groups. The protocol was completed by all participants without adverse events, supporting the feasibility of the procedure in this pilot sample. Its predictable scaling across baseline gait metrics supports its use as a personalized rehabilitation tool for diverse neurological populations. (ClinicalTrials.gov NCT07254377). Full article

Exoskeletons are increasingly used in industrial settings, yet most are designed for structured, repetitive tasks, limiting adaptability to dynamic movements. In construction, frequent locomotion tasks demand continuous lower-limb engagement, and ladder climbing places substantial loads on coordination and flexibility. This study aimed to identify key muscles involved in climbing to support the development of adaptive exoskeletons. Ten healthy male participants (33.8 ± 3.4 years; 178.7 ± 5.0 cm; 87.4 ± 16.1 kg) performed vertical and A-frame ladder ascents in a controlled laboratory setting. Surface electromyography was recorded from eight right-leg muscles and processed using band-pass filtering, rectification, and root mean square smoothing. Two normalization strategies were applied: walking normalization, expressing climbing activity relative to level walking, and maximum voluntary contraction normalization, with amplitudes expressed as a percentage of maximum voluntary contraction. Our results showed that all muscles were more active in climbing than walking, with quadriceps (vastus medialis, vastus lateralis, rectus femoris) exhibiting the greatest increases. Gastrocnemius also approached or exceeded 100%MVC, tibialis anterior averaged 70–80%MVC, and hamstrings contributed 20–40%MVC mainly for stabilization. Vertical and A-frame ladders followed similar patterns with subtle posture-related variations. These findings highlight knee extensors as primary targets for adaptive exoskeleton assistance during ladder climbing tasks commonly performed on construction sites. Full article