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The null-space projection method is commonly adopted for controlling redundant robots, which undoubtedly requires the robot Jacobian matrix inverse. This paper aims to provide a novel control scheme, which enables null-space control of redundant robots without conflict with the main task space.

In this paper, an impedance-based null-space control approach for redundant robots is proposed. The null-space degrees of freedom are separated from the primary task space by using the eigenvalue decomposition. Then, a joint impedance controller spans the null space and is reflected into the joint space to manage the redundancy. Finally, several experiments have been conducted to evaluate and validate the performance of the proposed approach in comparison with the null-space projection method under various situations.

Experiment results show that no significant differences were observed between the different filling eigenvalues in the proposed approach under different null-space dimensions and motion velocity. Besides, comparative experiment results demonstrate that the proposed method can achieve comparable results to the null-space projection method. Nevertheless, the suggested approach has benefits regarding the quantity of control parameters in addition to not requiring a Jacobian inverse. Notably, the performance of the proposed method will improve as the null-space dimension increases.

This study presents a new control method for redundant robots, which has advantages for dealing with the problems of controlling redundant robots compared to the existing methods.

This paper aims to investigate the impact of quality loss in transit on e-commerce supply chain pricing, production and financing decisions.

The authors consider a Stackelberg game model with a supplier, logistics firm and e-commerce platform. The logistics firm is capital-constrained and obtains funding from the e-commerce platform by debt financing or equity financing. Through backward induction, this paper first solves the equilibrium results under the two financing schemes and then reveals the financing preferences of all parties.

The results demonstrate that equity financing reduces financing costs and promotes production significantly. However, it may also lead to overproduction, particularly in markets with poor profitability and high cost factors. When the percentage of product quality loss is large, equity financing is preferable. With the increasing of transportation level, the benefits of debt finance are steadily growing. In addition, equity financing is the Pareto dominant scheme for all firms under certain circumstances. The extensions consider hybrid financing and another quality loss type.

The paper derives the equilibrium solutions and financing preferences, then specifies the threshold for applying financing schemes. Provide guidance for logistics firms’ finance model innovation and core enterprise involvement in the logistics industry.

The paper investigates how logistics firms’ financing strategies are impacted by product quality loss.

The influence of the temperature discrepancy parameter and higher order of the time-derivative is discussed. Classical coupled and generalized hygrothermoelasticity models are recovered by considering the various special cases and illustrated graphically.

The theory of integral transformations has been used to study a new hygrothermal model that includes higher-order time derivatives with three-phase-lags and memory-dependent derivatives (MDD). This model considers the microscopic structure’s influence on a non-simple hygrothermoelastic infinitely long cylinder. The generalized Fourier and Fick’s law was adopted to derive the linearly coupled partial differential equations with higher-order time-differential with the two-phase lag model, including memory-dependent derivatives for the hygrothermal field. The investigation of microstructural interactions and the subsequent hygrothermal change has been undertaken as a result of the delay time and relaxation time translations.

These two-phase-lag models are also practically applicable in modeling nanoscale heat and moisture transport problems applied to almost all important devices. This work will enable future investigators to gain insight into non-simple hygrothermoelasticity with different phase delays of higher order in detail.

To the best of my knowledge, and after completing an intensive search of the relevant literature, the author could not learn any published research that presents a general solution for a higher-order time-fractional three-phase-lag hygrothermoelastic infinite circular cylinder with memory memory-dependent derivative.

Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

One of the primary challenges associated with excavation near buildings is the significant decrease in the bearing capacity of nearby foundations during the initial stages before the stabilization of the excavation wall. This study aims to investigate the correlation between excavation height and foundation-bearing capacity under actual field conditions.

This paper uses a three-dimensional rotational failure mechanism to propose a novel method for estimating foundation-bearing capacity using the upper bound limit analysis approach.

The study delineates two distinct zones in the excavation height versus bearing capacity diagram. Initially, there is a significant reduction in foundation-bearing capacity at the onset of excavation, with decreases of up to 80% compared to its undisturbed state. Within a specific range of excavation heights, the bearing capacity remains relatively constant until reaching a critical height. Beyond this threshold, the entire soil mass behind the excavation wall becomes unstable. The critical excavation height is notably influenced by the soil's internal friction angle, excavation slope angle and soil cohesion parameter. Notably, when the ratio of excavation height to foundation width is less than 0.4, changes in slope angle have no significant impact on bearing capacity.

The bearing capacity estimates derived from the method proposed in this paper are deemed to reflect real-world scenarios closely compared to existing methodologies.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.

First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.

The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.

The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.

The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.

The spatial–temporal conflicts in the construction process of concrete arch dams are related to the construction quality and duration, especially for pouring blocks with a continuous high-strength and high-density construction process. Furthermore, the complicated construction technology and limited space resources aggravate the spatial–temporal conflicts in the process of space resource allocation and utilization, directly affecting the pouring quality and progress of concrete. To promote the high-strength, quality-preserving and rapid construction of dams and to clarify the explosion moment and influence degree of the spatial–temporal conflicts of construction machinery during the pouring process, a quantification method and algorithm for a “Conflict Bubble” (CB) between construction machines is proposed based on the “Time–Space Microelement” (TSM).

First, the concept of a CB is proposed, which is defined as the spatial overlap of different entities in the movement process. The subsidiary space of the entity is divided into three layered spaces: the physical space, safe space and efficiency space from the inside to the outside. Second, the processes of “creation,” “transition” and “disappearance” of the CB at different levels with the movement of the entity are defined as the evolution of the spatial–temporal state of the entity. The mapping relationship between the spatial variation and the running time of the layered space during the movement process is defined as “Time–Space” (TS), which is intended to be processed by a microelement.

The quantification method and algorithm of the CB between construction machinery are proposed based on the TSM, which realizes the quantification of the physical collision accident rate, security risk rate and efficiency loss rate of the construction machinery at any time point or time period. The risk rate of spatial–temporal conflicts in the construction process was calculated, and the outbreak condition of spatial–temporal conflict in the pouring process was simulated and rehearsed. The quantitative calculation results show that the physical collision accident rate, security risk rate and efficiency loss rate of construction machinery at any time point or time period can be quantified.

This study provides theoretical support for the quantitative evaluation and analysis of the spatial–temporal conflict risk in the pouring construction process. It also serves as a reference for the rational organization and scientific decision-making for pouring blocks and provides new ideas and methods for the safe and efficient construction and the scientific and refined management of dams.

The purpose of this paper is to solve the diverse and complex problems of flat-knitting sports upper process design, improve the design ability of upper organization, and realize three-dimensional simulation function.

Firstly, the matrix is used to establish the corresponding pattern diagram and organizational diagram model, and the relationship between the two is established by color coding as a bridge to completed the transformation of the flat-knitted sports upper process design model. Secondly, the spatial coordinates of the loop type value points are obtained through the establishment of loop mesh model, the index of two-dimensional and three-dimensional models of uppers and the establishment of spatial transformation relationship. Finally, using Visual Studio as a development tool, use the C# language to implement this series of processes.

Digitizing the fabric into a matrix model, combined with matrix transformation, can quickly realize the design of the flat-knitting process. Taking the knitting diagram of the upper process as the starting point, the loop geometry model corresponding to the element information is established, and the three-dimensional simulation effect of the flat-knitted upper based on the loop structure is realized under the premise of ensuring that it can be knitted.

This paper proposes a design and modeling method for flat-knitted uppers. Taking the upper design process and 3D simulation effect as an example, the feasibility of the method is verified, which improves the efficiency of the development of the flat-knitted upper product and lays the foundation for the high-end customization of the flat-knitted upper.