This research article presents a comprehensive design of operational strategies for robotic warehouses, a novel paradigm distinct from traditional manual and automated warehouse operations. The study introduces three independent strategies that address key operational tasks in robotic warehouses: product replenishment, shelf storage, and order-picking. Recognizing the interdependencies among these tasks, the research proposes a co-optimization approach and synchronization mechanism to harmonize the three strategies. This approach aims to align the strategies towards a common optimization objective, thereby enhancing the overall operational efficiency of the robotic warehouse. The cooperative optimization approach promotes synergy among the operational tasks, while the synchronization mechanism ensures that the tasks are executed in a coordinated manner, minimizing conflicts and maximizing efficiency. The research demonstrates that by integrating these strategies and applying the cooperative optimization and synchronization mechanism, significant improvements can be achieved in the operational efficiency of robotic warehouse.
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.
Preliminary research was conducted on the implementation approach and specific practices of aerospace cable process knowledge modeling according to the E3 model. The cable process E3 model application, process knowledge modeling methods and specific implementation cases were analyzed. Establishing a cable process knowledge modeling method based on the matching rules of E3 model data and process knowledge data, accomplishing the intelligent design of aerospace cable process, improving the design quality and efficiency of aerospace cable process models.
The digital twin is a vital technology for the intelligent manufacturing of proton exchange membrane fuel cell (PEMFC) stacks. Aiming to achieve an efficient optimal design for the stack assembly process, a digital twin modeling approach combining finite element analysis (FEA) and artificial neural network (ANN) is proposed in this paper. The establishing method of finite element model (FEM) for the stack under assembly conditions, the dataset construction method for FEM simulation results, and the modeling method of ANN for mechanical behavior prediction are systematically expounded. After that, the digital twin modeling solution is verified by a case study of the contact pressure prediction inside the stack. The results show that the ANN model based on the simulation dataset has a prediction accuracy close to 98% of the FEM, and the computational efficiency is improved more than tens of thousands of times. This model can also quickly obtain the entire stack uniformity at different compression ratios, which is a prerequisite for guiding the optimal design of the stack assembly process in production scenarios.
With the emergence of Smart Product Service Systems (SPSS), the construction of digital twin functional models has become a critical research area. This study aims to propose a comprehensive approach for constructing digital twin functional models specifically for SPSS. Currently, research on SPSS and digital twin technology primarily focuses on models and structures, with limited in-depth analysis of their functional dimensions. To address this gap, we propose a method that combines the functional models from Model-Based Systems Engineering (MBSE) with the flow analysis models, including material flow, information flow, and energy flow. By establishing correlations between the elements of the functional model and the flow model, we develop a comprehensive digital twin functional model. To validate the effectiveness of this method, we apply it to a diesel engine as a case study and successfully construct a comprehensive digital twin functional model for the system. The application of this construction method in the diesel engine case study confirms its effectiveness and feasibility, providing valuable insights for research and practice in the field of SPSS.
The comprehensiveness of functionality, controllability of processes, and advancement of technology are important in enterprise digitalization systems, but convenience and user-friendliness are even more crucial. Especially during the initial stage of implementing a digitalization system for small and medium-sized manufacturing enterprises, the creation of foundational data, particularly e-bill of material(e-BOM), plays a vital role. The ability to create the required e-bom determines the feasibility of running the digitalization system, and the efficiency of e-bom creation determines when the system can be operational. This paper proposes two approaches for batch creating material information based on relevant industries and application scenarios, which significantly improve efficiency compared to traditional methods. Among them, the batch creation approach for material information is particularly suitable for industries such as hardware, furniture, and injection molding, where the same component has different statuses. It improves the efficiency of material information creation by several times or even dozens of times. The intelligent batch creation approach for derivative materials, on the other hand, is especially useful for the creation of product information in industries such as ceramics (e.g., sanitary ceramics, dinner ware), hardware ware (e.g., faucets, showerheads, accessories), and stationery (e.g., erasers, pens, rulers), where the same product has different forms, specifications, colors, grades, trademarks, and other attributes. It improves the efficiency of material information creation by tens or even hundreds of times.
Long-term lubrication is a critical issue for the life of the momentum wheel bearings that operate under varying conditions. To solve this problem, the evolution law of bearing friction torque needs to be accurately obtained. This paper presents the design and evaluation of a novel tribo-test machine for the momentum wheel bearing using an environment-based design (EBD) methodology. The EBD methodology enables a targeted conceptual design that considers the actual working environment of the momentum wheel and defines the performance indicators of the testing machine. The testing machine consists of a drive module and a load module, and a test method for the calibration and measurement stages is proposed to eliminate the interference from non-target loads. The case study demonstrates the rationality and effectiveness of the EBD methodology in the innovative development of test instruments in the bearing field.
A picking robot is a standard agricultural robot. Agricultural picking operations are characterized by high labor demand and require a lot of physical strength and repetitive actions. Therefore, the development of picking robots has potential market demand and business opportunities, while factors such as robot cost, technical feasibility, and the ability to adapt to different crops and environments also need to be considered. Robotics is an important research area for bionic machines, and by combining the superior structure in biological systems with the properties of physics, humans may obtain bionic machines that are more complete in some properties than the systems formed in nature. Using Unigraphic software, a 3D model of the picking robot arm structure was created. Then, the model is imported into ANSYS Workbench, and modal and static analyses are performed on the model using finite element analysis methods. Thus, the robot arm structure is optimized and checked for feasibility. According to the results of the analysis, the equivalent stress and deformation distribution cloud diagram of the robot main structure model is obtained. Thus, the weaknesses of the bionic robot arm structure were identified and structural improvements were suggested. The results of the study provide a concrete basis for the rational design of the structural dimensions of the picking bionic robot arm.
In the context of the requirement for iterative updating of communication transmission modules in IoT applications, to address the problem that the baud rate in transmission needs to be agreed in advance and once agreed, it is not easy to be changed, this paper proposes a Universal Asynchronous Receiver/Transmitter (UART) communication system design based on adaptive baud rate technology, in order to implement the function of detecting and changing the transmission baud rate in the system. This design uses the level detection module to sample and count the check bits in a frame of data from a serial communication line, and uses the check bit eigenvalue matching method to get the serial communication baud rate of data, with the adjusted baud rates all being accurately detected and printed on the console. Thus, the slave receiver module can identify the current communication baud rate and make automatic adjustment to complete the data transmission. Software simulations and results demonstrate that: The design is simple to implement, fast, and takes up few resources.
The complex working environment may cause irreversible damage to sensors of robots. Constructing virtual sensor and working environment based on digital twin can reduce hardware damage and reduce production cost. Based on the architecture design of digital twinning system for ranging sensors, this paper conducts digital twinning modeling for ultrasonic and infrared ranging sensors, and investigates the application value of the digital twinning system. The motion environment, sensor reading module and motion control module in the physical world, as well as the motion environment, virtual sensor model program and motion control code in the virtual world are analyzed, and a complete digital twin operating environment is constructed. Different types of objects are selected to test the characteristics of the sensor, and main factors affecting the readings of the ultrasonic and infrared ranging sensors are determined. Then, the digital twin sensor is designed, and distance reading curves similar to those in reality can be obtained. Finally, the proposed ranging digital twin system is applied to the QBot3 mobile robot, the site is built in the real world, while the corresponding scene model is established based on QLab in the virtual world; and the stability and reliability of the system are tested.
Large-scale cargo Unmanned Aerial Vehicles (UAVs) have garnered significant attention as a promising innovation in the realm of delivery vehicles. In response to the potential congestion issues with UAVs, we design a hub-and-spoke network using multi-allocation and direct connection strategies. Two congestion optimization models consisting of a UAV logistics hub-and-spoke network with congestion waiting (ULCW) and a UAV logistics hub-and-spoke network with congestion redistribution (ULCR) are proposed based on a congestion cost function. Through case analysis, the effectiveness of the proposed models is demonstrated, with ULCR exhibiting superior performance.
For complex system, the integration of function knowledge from external design resources is the key to the integrity and reliability of the function design. However, the form and structure of unprocessed function knowledge are often hard to be directly applied to the integration and validation stages of function design. Due to the differentiated function cognition and disciplinary differences between fields, few complete function knowledge processing (FKP) methods have been developed so far. This paper proposes a FKP framework for complex system to support the efficient flow of function knowledge in design. The framework is applied to a design case of flight control system (FCS) to demonstrate the specific process of extraction, representation, integration and validation of function knowledge during the design process.
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.
The unmanned aircraft vehicle named shortly (UAV) functions akin to a programmed human brain, serving as a tool discovered by humans to overcome various challenges in life. As it excelled in its assigned tasks, researchers and developers began exploring the potential of utilizing swarms of UAVs to accomplish multiple tasks or even sub-tasks within a larger objective. To harness the benefits of these capabilities exhibited by UAV flocks, researchers devised different control strategies that focused on optimizing the distribution of swarm agents for optimal performance. Among these strategies, the leader-follower approach emerged as one of the most prominent and significant methods for distributing UAV flocks, which researchers have applied across various scenarios. In the present study, the objective is to investigate the optimal of the follower's position and distribution relative to the leader according the swarm's task. The researchers conducted a comparison of two distribution patterns and employed MATLAB to test the swarm's ability to navigate around static obstacles. The final results demonstrated that adopting a distribution pattern resembling the Diamond Formation “Triangle and M-shape distribution” with the leader yielded the best and least erroneous outcomes. Conversely, the Follower Formation “Linear Distribution” exhibited the poorest performance and the highest number of errors.
Spherical Robots, despite their unique structural advantages over other types of mobile robots, are still far from realizing their potential. In this paper, we analyze the causes of the slow development pace of the spherical robots and attribute it to the adoption of the conventional robot design roadmap by the research and engineering community for the development of these robots. To address this, we propose a new robot design roadmap, which we call “Test before Design” or in short “TBD”, which focuses on grasping the dynamics of the underlying drive units via experiments at the initial stage. We discuss the current key challenge in the spherical robots driven by two pendulums, which is mainly the dynamic modeling for the turning of the robot. Finally, we present the design of a simplified experimental setup to navigate through the ongoing key challenge in the development of spherical robots driven by two pendulums based on the TBD approach.
Flexoelectricity is related with a specific electromechanical coupling marvel between polarization and strain angles showing a promising estimate impact as the measurements of nanostructures decrease. This paper points to display a size-dependent investigation of micro-rotating circles made of practically reviewed piezoelectric (FGP) materials agreeing to the strain slope flexibility considering flexoelectric impacts. Agreeing to a power-law dissemination, mechanical and electrical properties are accepted to differ within the thickness direction. Herein, Gibbs free vitality thickness, which may be a work of strain, strain angle, and electric field, is utilized to infer the constitutive conditions. Two coupled electro-mechanical differential conditions in terms of outspread relocation and electric potential are extricated utilizing electric and mechanical equilibrium equations. The coupled differential conditions are illuminated utilizing the differential quadrature strategy (DQM), which could be a effective numerical discretization device. Numerical comes about appear the impacts of flexoelectric, strain angle parameter, non-homogeneity consistent, and precise speed on the size-dependent electro-mechanical reaction of the FGP micro-sphere. Too, a comparison think about between classic piezoelectricity and flexoelectricity-strain angle hypothesis is performed.
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.
In order to solve the problems of the existing grass grid paving machine, which destroys the existing turf and has low paving efficiency when working reciprocally, an automatic bidirectional grass grid paving vehicle is designed in this paper. In this paper, the functions of grass grid paving are studied and analyzed, and the machinery which can lay both horizontal and vertical turf at the same time is designed. The design mainly includes the mechanical execution part and the electric control part. In the mechanical part, the slotting functions are merged, and the design and layout of the executive mechanisms are streamlined. The electronic control system can realize the functions of obstacle detection, attitude detection, alarm, stress acquisition and so on. It uses the main control panel and the display screen to facilitate man-machine interaction. The model is built for verification, which shows that the mechanism and the electronic control system are scientific and that their functions are effective.
Nowadays, lighting has been widely used in production and life. Since people subconsciously produce different lighting impressions for different lighting, it is important to scientifically grasp users' deep impressions of various types of most common lighting in design research and apply them to the lighting design field. First, according to the characteristics of human design impressions formed by associative cognition, Word2vec big data semantic analysis tool is used to mine the natural language big data of human contact with the most common nine types of lighting deep impressions of associative vocabulary; second, through the centralized resonance analysis to obtain the semantic map of the nine common lighting; finally, the mined human deep impressions of the nine types of common lighting as the basis for lighting; lastly, the unearthed deep impressions of the nine common lighting categories are used as the basis for lighting design practice. The research results can provide a reference basis for future lighting design and ambience creation of various types of lighting environments, and meet the design needs of a wide range of users for lighting products.
This paper is interested in a numerical method, we use the mini-element ${P}_{1}$-Bubble/P1 over triangles, as a solver to the steady Brinkman flow equation with the Dirichlet boundary condition in a heterogeneous porous media. We define the necessary hypotheses to prove the existence and uniqueness of the solution. An iterative solver for the global linear system (Uzawa conjugate gradient method) is applied to accelerate the approach solution. A series of numerical examples with Matlab software demonstrates the effectiveness of this method for these equations arising in modeling flow in anisotropic porous media.
