Xiaojun Wu

Multi-terrain adaptability and metabolic reduction are critical for translating load-carrying lower-limb exoskeletons into practical use. However, conventional single-mode sensing cannot synchronously quantify human–exoskeleton interaction forces and physiological metabolic responses across complex terrains. To address this limitation, this study develops a rigid–flexible coupled load-carrying lower-limb exoskeleton and constructs a dual-modal test platform for interaction force and metabolic energy expenditure. Using DYMH-102 diaphragm box load cells and the Cosmed K5 portable gas metabolism analyzer, a standardized outdoor multi-scenario sensing protocol is established. This protocol quantifies exoskeleton assistance performance and human metabolic benefits under a 15 kg load over three representative terrains: hard level ground (HLG), gently uneven grassland (GUG), and gently sloped mountain road (GMR). The experimental results show that terrain complexity directly affects sensor measurement outcomes and exoskeleton assistance performance: under the three terrain conditions, the shoulder load transfer efficiencies of the exoskeleton are 55.97%, 54.76%, and 42.45%, respectively, and the peak impact load reduction rates reach 78.26%, 80.00%, and 66.67%. A descriptive gradual decline in metabolic saving was observed, likely attributable to terrain perturbations, gait distortion, and human–machine interface slippage, with metabolic cost reductions of 16.28%, 11.93%, and 11.48%. Unlike conventional exoskeleton evaluations relying on isolated performance metrics, this work integrates mechanical and physiological dual-modal sensing to create a synchronous quantitative assessment method for wearable devices in complex outdoor environments. The proposed method mitigates the poor terrain adaptability and lack of multi-parameter coupled evaluation that plague current wearable biosensing systems.

Accurate traffic flow prediction is the basis of urban traffic guidance and control, which is of great significance to intelligent traffic management and control. The complex spatial and temporal dependencies of traffic flow, as well as the periodicity and spatial heterogeneity of capturing traffic data, make accurate traffic flow prediction still a major challenge. To address the above problems, this article proposes DGCN-STA, a dynamic graph convolutional network for traffic flow prediction based on a spatio-temporal attention mechanism. Specifically, in the time dimension, this article constructs a new self-attention mechanism that can utilize local contexts, specifically for numerical sequence representation transformation, so that the prediction model is able to capture the temporal correlation of traffic flow, which is conducive to long-term prediction. In the spatial dimension, a dynamic graph convolution method is constructed to capture spatial correlations in a dynamic manner using self-attention, modeling for the periodicity of traffic flows and capturing spatial heterogeneity through embedding modules. The spatio-temporal correlation of long time series is then modeled using the spatio-temporal attention mechanism. Many experiments are conducted on four datasets, and the experimental results show that the DGCN-STA model proposed in this article has better prediction performance compared with the baseline method.

Lower limb exoskeletons significantly enhance human functionality. However, simultaneously improving the load capacity of these devices while reducing metabolic costs presents a major challenge in the industry. This paper presents a lower limb exoskeleton that integrates both rigid and flexible structures to facilitate active assistance and passive load transfer at the hip joint. The load transfer experiments were conducted with weights of 10 kg and 15 kg. During static standing, the load transfer rates were recorded at 90.48% and 69.70%, respectively. In dynamic walking, these rates decreased to 62.07% and 43.69%. Furthermore, in metabolic experiments involving a load of 15 kg, metabolic costs in the exoskeleton assistance modes OFF (Assist OFF) and exoskeleton assistance ON (Assist ON) were reduced by 8.3% and 21.61%, respectively, compared to the exoskeleton-free condition (NE). Furthermore, the Assist ON mode further decreased metabolic costs by 13.22% compared to the Assist OFF mode. These findings demonstrate that the rigid-soft coupled lower limb exoskeleton exhibits exceptional load transfer capabilities and effective assistance, highlighting its potential to enhance human performance in weight-bearing activities.

The phase detection of abnormal gait and the prediction of lower-limb angles are key challenges in controlling lower-limb exoskeletons. This study simulated three types of abnormal gaits: scissor gait, foot-drop gait, and staggering gait. To enhance the recognition capability for abnormal gait phases, a four-discrete-phase division for a single leg is proposed: pre-swing, swing, swing termination, and stance phases. The four phases of both legs further constitute four stages of walking. Using the Euler angles of the ankle joints as inputs, the capabilities of a Convolutional Neural Network and a Support Vector Machine in recognizing discrete gait phases are verified. Based on these discrete gait phases, a continuous phase estimation is further performed using an adaptive frequency oscillator. For predicting the lower-limb motion angle, this study innovatively proposes an input scheme that integrates three-axis ankle joint angles and continuous gait phases. Comparative experiments confirmed that this information fusion scheme improved the limb angle prediction accuracy, with the Convolutional Neural Network–Long Short-Term Memory network yielding the best prediction results.

Inspired by the fact that flying insects improve their power conversion efficiency through resonance, many soft robots driven by dielectric elastomer actuators (DEAs) have achieved optimal performance via first-order modal resonance. Besides first-order resonance, DEAs contribute to multiple innovative functions such as pumps that can make sounds when using multimodal resonances. This study presents the multimodal resonance of a rectangular planar DEA (RPDEA) with a central mass bias. Using a combination of experiments and finite element modeling (FEM), it was discerned that under a prestretch of 1.0 × 1.1, the first-, second-, and third-order resonances corresponded to vertical vibration, rotation along the long axis, and rotation along the short axis, respectively. In first-order resonance, superharmonic, harmonic, and subharmonic responses were activated, while only harmonic and subharmonic responses were observed in the second- and third-order resonances. Further investigations revealed that prestretching tended to inhibit third-order resonance but could elevate the resonance frequencies of the first and second orders. Conveniently, both the experimental and FEM results showed that the frequencies and amplitudes of the multimodal resonances could be tuned by adjusting the amplitudes of the excitation signals, referring to the direct current (DC) amplitude and alternating current (AC) amplitude, respectively. Moreover, instead of linear vibration, we found another novel approach that used rotation vibration to drive a robot with soft bristles via hopping locomotion, showcasing a higher speed compared to the first-order resonance in our robot.

Biologically inspired pneumatic ring-shaped soft grippers have been extensively studied in the field of soft robotics. However, the effect of the number of air chambers on the grasping performance (grasping range and load capacity) of ring-shaped soft grippers has not been studied. In this article, we propose three ring-shaped soft grippers with the same area of inner walls of air chambers and different numbers of air chambers (two-chamber, three-chamber, and four-chamber) for analyzing and comparing their grasping performance. Finite element method (FEM) models and experimental measurements are conducted to compare the deformation of the inner walls of the three ring-shaped soft grippers, the results indicate that the grasping range of the three-chamber ring-shaped soft gripper is larger than that of the two-chamber ring-shaped soft gripper and the four-chamber ring-shaped soft gripper. Then we choose the three-chamber ring-shaped soft gripper to study the relationship between contact force and air pressure by FEM models and experimental measurements. Several groups of experiments are constructed to compare the load capacity of the three ring-shaped soft grippers, the results indicate that the load capacity of the three-chamber ring-shaped soft gripper is higher than that of the two-chamber ring-shaped soft gripper and the four-chamber ring-shaped soft gripper. The above results reveal that the grasping performance of the three-chamber ring-shaped soft gripper is better than that of other two ring-shaped soft grippers. Furthermore, the application experiments indicate that the three ring-shaped soft grippers can grasp various objects with different weights, material properties, and shapes. This study provides a new idea for investigating ring-shaped soft grippers.

Background: Airway stent has been widely used in airway procedures. However, the metallic and silicone tubular stents are not customized designed for individual patients and cannot adapt to complicated obstruction structures. Other customized stents could not adapt to complex airway structures with easy and standardized manufacturing methods.Object: This study aimed to design a series of novel stents with different shapes which can adapt to various airway structures, such as the “Y” shape structure at the tracheal carina, and to propose a standardized fabrication method to manufacture these customized stents in the same way.Methods: We proposed a design strategy for the stents with different shapes and introduced a braiding method to prototype six types of single-tube-braided stents. Theoretical model was established to investigate the radial stiffness of the stents and deformation upon compression. We also characterized their mechanical properties by conducting compression tests and water tank tests. Finally, a series of benchtop experiments and ex vivo experiments were conducted to evaluate the functions of the stents.Results: The theoretical model predicted similar results to the experimental results, and the proposed stents could bear a compression force of 5.79N. The results of water tank tests showed the stent was still functioning even if suffering from continuous water pressure at body temperature for a period of 30 days. The phantoms and ex-vivo experiments demonstrated that the proposed stents adapt well to different airway structures.Conclusion: Our study offers a new perspective on the design of customized, adaptive, and easy-to-fabricate stents for airway stents which could meet the requirements of various airway illnesses.

Confined space searches such as pipeline inspections are widely demanded in various scenarios, where lightweight soft robots with inherent compliance to adapt to unstructured environments exhibit good potential. We proposed a tubular soft robot with a simple structure of a spring-rolled dielectric elastomer (SRDE) and compliant passive bristles. Due to the compliance of the bristles, the proposed robots can work in pipelines with inner diameters both larger and smaller than the one of the bristles. Firstly, the nonlinear dynamic behaviors of the SRDE were investigated experimentally. Then, we fabricated the proposed robot with a bristle diameter of 19 mm and then studied its performance in pipelines on the ground with inner diameters of 18 mm and 20 mm. When the pipeline’s inner diameter was less than the outer diameter of the bristles, the bristles remained in the state of bending and the robot locomotion is mainly due to anisotropic friction (1.88 and 0.88 body lengths per second horizontally and vertically, respectively, in inner diameter of 18 mm and 0.06 body length per second in that of 16 mm). In the case of the pipeline with the larger inner diameter, the bristles were not fully constrained, and a small bending moment applied on the lower bristle legs contributed to the robot’s locomotion, leading to a high velocity (2.78 body lengths per second in 20 mm diameter acrylic pipe). In addition, the robot can work in varying geometries, such as curving pipes (curve radius ranges from 0.11 m to 0.31 m) at around two body lengths per second horizontally and on the ground at 3.52 body lengths per second, showing promise for pipeline or narrow space inspections.

Pneumatic soft grippers have been widely studied. However, the structures and material properties of existing pneumatic soft grippers limit their load capacity and manipulation range. In this article, inspired by sea lampreys, we present a pneumatic novel combined soft gripper to achieve a high load capacity and a large grasping range. This soft gripper consists of a cylindrical soft actuator and a detachable sucker. Three internal air chambers of the cylindrical soft actuator are inflated, which enables them to hold objects. Under vacuum pressure, the cylindrical soft actuator and the detachable sucker can both adsorb objects. A finite element model was constructed to simulate three inflation chambers for predicting the grasping range of the cylindrical soft actuator. The validity of the finite element model was established by an experiment. The mechanism of holding force and adsorption force were analyzed. Several groups of experiments were conducted to determine adsorption range, holding force, and adsorption force. In addition, practical applications further indicated that the novel combined soft gripper has a high load capacity (10.85 kg) at a low pressure (16 kPa) and a large grasping range (minimum diameter of the object: d = 6 mm), being able to lift a variety of objects with different weights, material properties, and shapes.