Spherical robots, characterized by their unique fully enclosed spherical structures, offer enhanced mobility and robust operation in challenging environments and adverse weather conditions. This paper presents the design and control of a dual-degree-of-freedom pendulum-driven spherical robot, addressing key limitations of conventional designs such as large turning radii and inadequate slope-climbing capabilities. The influence of the pendulum’s eccentric mass on climbing performance and obstacle-crossing ability is systematically analyzed, leading to a novel structural design approach. A comprehensive dynamic model is established, decoupling the robot’s motion into linear and steering components to facilitate control system development. Building upon this model, an Adaptive High-Speed Sliding Mode Control (AHSMC) strategy is proposed to achieve rapid response and robust trajectory tracking under highly nonlinear dynamics. Experimental validations demonstrate a minimum turning radius of 0.2 meters and stable operation on slopes up to 12 ^∘ . Moreover, the AHSMC-based velocity control outperforms traditional PID and hierarchical sliding mode control (HSMC) methods in terms of speed regulation accuracy and robustness, enabling precise trajectory tracking across both smooth and asphalt surfaces. The results substantiate the effectiveness of the proposed design and control framework, underscoring its potential for practical deployment in dynamic and constrained environments typical of small-scale robotics applications.

Aiming at the problems of complex and harsh working environments and low reliability of the working arm of the anchor drilling robot, the dynamic characteristics of the working arm are studied based on the dynamic simulation analysis and vibration test analysis. In view of the influence of working load and deformation on the rigidity of the working arm, the static finite element analysis is implemented by simulating the actual working conditions. The stress and strain distribution of the working arm under the roof anchor drilling condition is derived, and on this basis, the modal analysis of the working arm with pre-stress is carried out. The six orders of vibration mode and the corresponding inherent frequencies are obtained. A vibration test system of the working arm is set up to achieve the three-dimensional vibration accelerations of the working arm under the roof anchor drilling condition. The fast Fourier transform of the vibration acceleration signals is conducted to obtain the vibration spectrum. The dynamic characteristics of the working arm are analyzed through the vibration frequency and the inherent frequency, which is of great reference value for improving the reliability of the working arm.

To gain insight into the real-world black carbon (BC) emission patterns at urban intersections, we employed a portable emission measurement system (PEMS) to assess the BC emissions from three light-duty gasoline vehicles along a designated urban route. The BC emission factors were evaluated, and the contributions of vehicle operating conditions at the intersections to the total BC emissions were quantified. The results show that the BC emission factors in an intersection area range from 0.045 to 0.291 mg/km, higher than those at an intersection's connecting sections. The average BC emission factor at signalized intersections is 17.07% higher than at roundabouts. Emission contribution analysis of driving conditions showed that in a state of non-free traffic flow, acceleration and deceleration conditions are responsible for 39% - 56% and 24% - 33% of BC emissions at intersections, respectively. We also found that vehicle specific power (VSP) and delay time are almost equally crucial for BC emissions from vehicles at intersections in the multiple linear regression. Our research reveals the significant impact of vehicle delay time and acceleration conditions on black carbon emissions at urban intersections, further emphasizing the importance of smooth (congestion-free) intersection operation and steady driving in reducing urban black carbon emissions.

Urban Black Carbon (BC) emissions from light-duty gasoline vehicles (LDGVs) are challenging to quantify in real-world settings. This study employed a Portable Emission Measurement System (PEMS) to assess BC emissions from five LDGVs on urban roads. We also developed five machine learning (ML) models based on On-Board Diagnostics (OBD) data to predict BC emissions. Among these, the Random Forest (RF) model consistently demonstrates the best ability to predict BC emissions across all tested LDGVs, with R2 values exceeding 0.6. Integrating OBD-based ML models within vehicles could enable real-time BC monitoring and aid emission reduction strategies. We observed a strong correlation between BC emissions and engine parameters, such as engine speed and load (R2 values between 0.5 and 0.9). Furthermore, China VI standard-compliant LDGVs showed minor differences in BC emissions across urban road types. Vehicles equipped with gasoline direct injection (GDI) engines registered BC emission factors (EFs) of 0.141 ± 0.038 mg/km, an increase of 23.7% compared to their port fuel injection (PFI) counterparts, which averaged 0.114 ± 0.049 mg/km.

Abstract High power centrifugal pump is frequently used in large project for water resources allocation. Cavitation phenomenon causes noise and vibration and affects the centrifugal pump unit stability. The impeller model was used an initial impeller to be developed, and the impeller geometry, the blade profile, blade inlet edge were optimized by design method based on numerical simulation technique to improve cavitation performances. The 3D model with the initial and optimized impeller were simulated to obtain cavitation characteristic. The results of optimization impeller are compared and verified by model test. The numerical simulation results show that the pressure distribution is distributed on the blade surface is uniform and the location of lowest pressure is reasonable. The test results show that the optimized design significantly increases the ratio of plant cavitation coefficient σp to incipient cavitation coefficient σi and critical cavitation coefficient σ1 of the impeller under normal operation conditions, the safety margin of cavitation is increased. It was confirmed from numerical simulation and model test results that the impeller blade optimization is a reasonable and effective method for cavitation performance improvement. The study results provides design reference for the cavitation performance improvement and safe operation of high power centrifugal pump.

The research on the knee joint moment measurement method is of great significance for the moment control and efficiency measurement of the assisted exoskeleton. For most of the existing measuring methods are not suitable when wearing the assisted exoskeleton, knee joint moment measuring methods of assisted exoskeleton system based on Back-propagation (BP) neural network and Long short term memory (LSTM) neural network is proposed, in which surface EMG to joint moment mapping model is created. The estimation of knee moment at different load levels is realized. The experiment of human walking with a natural gait is verified. The root mean square error of the prediction is less than 17%, and the correlation coefficient is above 0.95.

In response to the prevalent social issue of elderly individuals living alone who lack independent mobility and face difficulties in standing up and getting up, a multi-modal intelligent elderly assistance wheelchair robot has been developed to provide assistance in such scenarios. This paper presents the analysis of the assistance needs of the elderly, along with the proposed main functions of the robot. The mechanical structure of the robot was designed and verified through finite element analysis, followed by experimental verification of assisted standing, transformation of bed and chair form, assisted getting up, and knee-free bending assisted getting up functions. The results of the experiments demonstrate that the multi-modal intelligent wheelchair robot developed in this study can effectively assist the elderly living alone in completing the actions of getting up and standing, thereby reducing their physical burden in home activities and improving their quality of life. This development has potential for broader applicability in the field of elderly care.

Gait rehabilitation is critical for postoperative rehabilitation to improve the quality of life in people with unilateral knee injuries. Although some studies have studied the effects of using rehabilitation exoskeletons for patients rehabilitation, the improvement of patient gait quality with a single knee exoskeleton has not been thoroughly investigated. In this study, a deep neural network-based biological torque controller is presented for realtime control of the unilateral knee exoskeleton. The aim was to improve the gait quality of patients by enhancing their gait symmetry. A lightweight unilateral knee exoskeleton system with low passive impedance and well transparent was used to develop and validate the controller during both treadmill and level walking modes. The proposed control strategy is characterized by accurate assisted output torque even when the motion pattern is changed, and does not require controller parameter adjustment. To test it, five able-bodied subjects used an exoskeleton with an artificial blocking device at the knee joint position that simulated the patient’ s defective postoperative pathological gait(i.e., reduced knee flexion). The subjects walked continuously on a treadmill and a flat surface. The experimental results demonstrated that the control strategy effectively improved the gait quality of the participants.

The motor grader is a high-speed travelling-type earth-moving machine widely used in infrastructure construction, of which the working device is driven by the travelling system to overcome the working load. At present, the power shift gear transmission is the major driving mode of high-power motor graders, yet the application of hydrostatic driving in travelling system is also of great research value and worth continuous exploration due to its unique advantages. In this paper, design of the open-loop and the closed-loop hydrostatic travelling systems of the motor grader is studied and compared by theoretical analysis, simulation and test. Firstly, the structure and the working principle of the two systems are introduced, and the acceleration performance, braking performance and the efficiency are calculated and compared quantitatively. Secondly, the simulation models of these two systems are built in AMESim software, and the simulation are carried out under two typical working conditions, i.e. starting and stopping processes. Next, the difference and the causes are discussed based on the test analysis of the performance of acceleration time, stopping distance, anti-drag phenomenon, peak pressure and suction of both the two systems. Finally, from the perspective of functionality, performance and manufacture cost, the advantages and the disadvantages of the two systems are summarized.

Knee exoskeletons have great potential in gait training and intervention for patients with knee osteoarthritis after surgery. Traditional single-axis rigid exoskeletons suffer from issues such as large joint volume, high inertia, and joint misalignment, significantly reducing wearer comfort. Soft exoskeletons can reduce the size and weight of artificial joints but lose the load support and mechanical limiting capabilities of rigid structures. This paper proposes a novel hybrid rigid-soft knee exoskeleton that employs a cross four-bar mechanism with loaded springs to mimic the multi-rotational center motion of the knee joint, avoiding joint misalignment and reducing the driving energy consumption of the exoskeleton. A genetic algorithm is used to optimize the structural parameters of the links and the stiffness coefficients of the springs by minimizing a weighted cost function composed of the deviation between the exoskeleton's rotation center and the user's knee joint, as well as the total potential energy of the system. Finally, a kinematic simulation is conducted to determine the linear relationship between the knee joint angle and the motor angle.

There has been growing interest in the development of exosuit-assisted locomotion to effectively assist human motion. In this study, we present a novel soft ankle joint exosuit capable of providing dynamic support in varying terrains. The exosuit's underdriven structural design, combined with the use of visual sensors for real-time environmental detection, distinguishes it from existing solutions. The underdriven design enables the exosuit to achieve two degrees of freedom using a single actuator, thus improving its mobility and functionality. Additionally, we employ a semantic segmentation model based on deep learning to recognize the terrain of the environment and adapt the exosuit's assistance accordingly. The visual sensors provide real-time information to the system, allowing it to switch between assisted states and improve the exosuit's overall performance. We carried out experiments on a prototype to validate our proposed approach. With 83% accuracy of terrain recognition, the results demonstrate its feasibility and potential for future development.

Drawing on extant literature on hexapod robots, we present a novel obstacle-crossing hexapod robot that can adapt to multiple terrains. We designed the robot's entire mechanical structure, established a mathematical model for the robot leg, deduced the kinematic equation of the leg, and determined the relationship between the robot's motion speed and the motor angle. Through force analysis of the C-shaped leg, we obtained the function between motor output torque and motion phase. Subsequently, we constructed the physical hexapod robot and conducted performance testing. Our experimental results demonstrate that the hexapod robot can move at a speed of 0.5 m/s and successfully cross a 10 cm obstacle. The robot exhibits excellent movement performance and satisfies the functional requirements. Overall, our design offers a promising approach for developing hexapod robots that can navigate a variety of terrains.

With the development of spaceflight, a strong demand for research on human activities in low-gravity or completely weightless environments in space has emerged. In this paper, a novel weight reduction system is designed to simulate astronauts walking in low-gravity environment. Based on the perfect static gravity balance, the system combines an active compensation strategy in which the wire tension mechanism drives the trunk support platform to assist people through wire-driven double parallelogram linkage. Passive balance is used to compensate partial weight of the body, and active control is used to achieve dynamic balance during the motion. In addition, static and dynamic balance control is used to evaluate the static and dynamic performance of the weight reduction system. The simulation results show that the system can significantly reduce the lower limb joint moments and ground reaction forces of the subjects, which verifies the feasibility of the system to simulate a low-gravity environment.

In the urban traffic research field, taxi detour behavior analysis can be regarded as one of the most crucial and challenging topics accounting for real-world routing network dynamics with complicated external inducement such as “avoiding congestion sections”, “unfamiliarity with road maps” or just “earning more fee under a longer travel path”. We carried out an interdisciplinary research framework to build a more holistic and profound view of the spatio-temporal distribution of the taxi detour behavior at directional road segment (DRS) level. First, a map matching based detour clustering method was proposed to deal with one week of taxi GPS tracing (divided into 3.4 million occupied trips). Then we employed an established multi-layer road index system in Shenzhen, China, to illustrate the spatio-temporal distribution variation of taxi detour features and statistics. Furthermore, three categories of DRS factors related to road structural attributes, traffic dynamics and point-of-interests (POIs) were defined to fit a selected-sample-based binary logit model. Some remarkable findings include: (i) in Shenzhen on average, 23.5 percent of taxi trips made a detour larger than 2.1 kilometers, which could be astonishingly high considering that only a very few trips yielded formal complaints for fraudulent detouring; (ii) both the level of detour intensity and ratio are affected by road features and dynamics in different spatio-temporal interaction patterns.

压路机作为道路压实设备,具有工况恶劣、循环作业及工作繁重等特点,长时间施工不仅影响身体健康,还会导致作业质量下降.无人驾驶技术对于解决这一问题具有重要的实际意义.为了实现压路机的无人驾驶及自动作业,建立了包括直线及换道曲线两部分的压路机作业轨迹模型,采用贝塞尔曲线设计了换道轨迹,并以曲率和曲率的变化率为约束,对换道轨迹曲线进行优化.

Cycling benefits both the individual and society in terms of public health promotion, traffic congestion relief and vehicle emissions reduction. To better understand cycling behaviors, we analyze non-linear relationships and interaction effects between the built environment and cycling distance. Few studies explore the interaction effects on cycling distance in which road network patterns interact with the demographic, trip, and other built environment characteristics to produce complex effects. Previous research has not examined the effect size or relative contribution of various variables have on cycling distance. Thus, this study adopts eXtreme Gradient Boosting (XGBoost) to examine the non-linear relationships among road network patterns, demographic, trip, and bike lane infrastructure, and other built environment characteristics and cycling distance, and employs SHapley Additive exPlanations (SHAP) to discover complex interaction effects on cycling distance, based on a bike travel survey in Xi'an, China. The results show that road network patterns have the greatest contribution; bike lane infrastructure is also quite important and has larger collective contributions than land use patterns and socioeconomics. Average geodesic distance and network betweenness centrality, two topological indices to describe road network structure, interact with bike lane infrastructure, land use and demographic characteristics to produce interaction effects on explaining cycling behaviors. When the average geodesic distance is smaller than 2.8 and the network betweenness centrality is smaller than 50%; as average geodesic distance increases, the network betweenness centrality has a positive effect on cycling distance. A network with a lower average geodesic distance, and with a higher intersection density makes cyclists ride a longer distance. A network with a higher value of average geodesic distance discourages cyclists to detour.

This paper presents a high-speed aero-fuel centrifugal pump with an active inlet injector for an aero-engine aiming at regulating the internal flow field and improving overall hydraulic performance. Unlike most of the existing centrifugal pumps for aero-engines, an injector is designed and integrated with the pump to accomplish the active flow control. Firstly, by employing the energy equation in the pump, reasonable geometrical parameters of the injector are calculated. Then, a validation study is conducted with three known turbulence models, showing that simulations with the RNG κ-ε turbulence model can accurately predict the head and efficiency of the experimental pump. Finally, simulation results with the determined turbulence model are discussed. The results show that the static pressure is uniformly distributed inside the impeller, the volute and the injector. The flow field is significantly ameliorated by improving the pressure inside the suction pipe and controlling the flow direction via the injector. Furthermore, the head and efficiency of the designed pump with an active inlet injector are improved compared to the one without an injector.

作为道路修筑的一种最终压实设备,轮胎压路机具有较大的作业质量和频繁起步一碾压一制动的循环作业特点.如果在轮胎压路机起步与制动过程中对加/减速度控制不当,会造成惯性负载过大,从而导致路面压实不均匀,严重时甚至引起铺层推移或拥包,并影响最终成形路面的质量.为减小惯性负载对轮胎压路机施工作业的影响,提出以沥青混凝土铺层被破坏的极限受力为阈值获取最大允许加/减速度,并依此对惯性负载进行控制的方法.首先对轮胎压路机的起步与制动过程进行动力学分析,计算沥青混凝土铺层间的临界剪切力、沥青混凝土铺层与基层之间的临界剪切力和压路机临界滑转状态的驱动力/制动力;然后以沥青混凝土铺层不发生受力破坏为目标,将3种极限工况中最小受力值确定为最大允许驱动力/制动力,并依此给出起步与制动过程中加/减速度的最大允许值.讨论平均加速度与最大加速度的关系,并提出轮胎压路机行驶控制中加/减速度的综合控制策略.

Aero-fuel centrifugal pumps are important power plants in aero-engines. Unlike most of the existing centrifugal pumps, a combination impeller is integrated with the pump to improve performance. First, the critical geometrical parameters of the combination impeller and volute are given. Then, the effects of the combination impeller on the flow characteristics of the impeller and volute are clarified by comparing simulation results with that of the conventional impeller, where the effectiveness of the selected numerical method is validated by an acceptable agreement between simulation and experiment. Finally, the experiment is set to test the external performance of the studied pump. A significant feature of this study is that the flow characteristics are significantly ameliorated by reducing the flow losses that emerged in the impeller inlet, impeller outlet, and volute tongue. Correspondingly, the head and efficiency of a combination impeller are higher with comparison to a conventional impeller. Consequently, it is a promising approach in ameliorating the flow field and improving external performance by applying a combination impeller to an aero-fuel centrifugal pump.

Road conditions are of critical importance for motion control problems of the autonomous vehicle. In the existing studies of Model Predictive Control (MPC), road condition is generally modeled with the system dynamics, sometimes simplified as common disturbances, or even ignored based on some assumptions. For most of such MPC formulations, the cost function is usually designed as fixed function and has no relations with the time-varying road conditions. In order to comprehensively deal with the uncertain road conditions and improve the overall control performance, a new model predictive control strategy based on a mechanism of adaptive cost function is proposed in this paper. The relation between the cost function and road conditions is established based on a set of priority policies which reflect the different cost requirements under different road grades and friction coefficients. The adaptive MPC strategy is applied to solve the longitudinal control problem of autonomous vehicles. Simulation studies are conducted on the MPC method with both the fixed cost function and the adaptive cost function. The results show that the proposed adaptive MPC approach can achieve a better overall control performance under different road conditions.