A Reverse Path Planning Approach for Enhanced Performance of Multi-Degree-of-Freedom Industrial Manipulators

In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking.While Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion optimization.Achieving satisfactory results in practical scenarios remains challenging.In response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial manipulators.The approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free path.To enhance convergence speed,the Q-learning algorithm in RL is augmented with Dyna-Q.Additionally,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection technique.Furthermore,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power joints.The efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target positions.Experimental results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target point.Moreover,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.

Eco-city Planning and Practices from the Perspective of Environmental Performance Evaluation

By reviewing researches on environmental performance evaluation of current eco-city construction, this paper analyzed characteristics and deficiencies of the evaluation methods and index systems, and took Haizhu Eco-city for example to assess the environmental performance of eco-city construction from the perspectives of land, water environment, regional weather, and biodiversity. On this basis, a scientific, objective and feasible evaluation method and index system was basically formed so as to demonstrate the efficiency of eco-city construction, and to provide scientific support for the dynamic adjustment and optimization of eco-city construction.

Effects of thinning on the understory light environment of different stands and the photosynthetic performance and growth of the reforestation species Phoebe bournei

Light levels determine regeneration in stands and a key concern is how to regulate the light environment of different stand types to the requirements of the understory.In this study,we selected three stands typical in south China(a Cryptomeria japonica plantation,a Quercus acutissima plantation,and a mixed stand of both)and three thinning intensities to determine the best understory light environ-ment for 3-year-old Phoebe bournei seedlings.The canopy structure,understory light environment,and photosynthe-sis and growth indicators were assessed following thin-ning.Thinning improved canopy structure and understory light availability of each stand;species composition was the reason for differences in the understory light environ-ment.Under the same thinning intensity,the mixed stand had the greatest light radiation and most balanced spectral composition.P.bournei photosynthesis and growth were closely related to the light environment;all three stands required heavy thinning to create an effective and sustained understory light environment.In a suitable understory light environment,the efficiency of light interception,absorption,and use by seedlings was enhanced,resulting in a higher carbon assimilation the main limiting factor was stomatal conductance.As a shade-avoidance signal,red/far-red radia-tion is a critical factor driving changes in photosynthesis and growth of P.bournei seedlings,and a reduction increased light absorption and use capacity and height:diameter ratios.The growth advantage transformed from diameter to height,enabling seedlings to access more light.Our findings suggest that the regeneration of shade-tolerant species such as P.bournei could be enhanced if a targeted approach to thinning based on stand type was adopted.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Motion Planning for Autonomous Driving with Real Traffic Data Validation

Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.

Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints

The problem of prescribed performance tracking control for unknown time-delay nonlinear systems subject to output constraints is dealt with in this paper. In contrast with related works, only the most fundamental requirements, i.e., boundedness and the local Lipschitz condition, are assumed for the allowable time delays. Moreover, we focus on the case where the reference is unknown beforehand, which renders the standard prescribed performance control designs under output constraints infeasible. To conquer these challenges, a novel robust prescribed performance control approach is put forward in this paper.Herein, a reverse tuning function is skillfully constructed and automatically generates a performance envelop for the tracking error. In addition, a unified performance analysis framework based on proof by contradiction and the barrier function is established to reveal the inherent robustness of the control system against the time delays. It turns out that the system output tracks the reference with a preassigned settling time and good accuracy,without constraint violations. A comparative simulation on a two-stage chemical reactor is carried out to illustrate the above theoretical findings.

Design of low-alloying and high-performance solid solution-strengthened copper alloys with element substitution for sustainable development

Solid solution-strengthened copper alloys have the advantages of a simple composition and manufacturing process,high mechanical and electrical comprehensive performances,and low cost;thus,they are widely used in high-speed rail contact wires,electronic component connectors,and other devices.Overcoming the contradiction between low alloying and high performance is an important challenge in the development of solid solution-strengthened copper alloys.Taking the typical solid solution-strengthened alloy Cu-4Zn-1Sn as the research object,we proposed using the element In to replace Zn and Sn to achieve low alloying in this work.Two new alloys,Cu-1.5Zn-1Sn-0.4In and Cu-1.5Zn-0.9Sn-0.6In,were designed and prepared.The total weight percentage content of alloying elements decreased by 43%and 41%,respectively,while the product of ultimate tensile strength(UTS)and electrical conductivity(EC)of the annealed state increased by 14%and 15%.After cold rolling with a 90%reduction,the UTS of the two new alloys reached 576 and 627MPa,respectively,the EC was 44.9%IACS and 42.0%IACS,and the product of UTS and EC(UTS×EC)was 97%and 99%higher than that of the annealed state alloy.The dislocations proliferated greatly in cold-rolled alloys,and the strengthening effects of dislocations reached 332 and 356 MPa,respectively,which is the main reason for the considerable improvement in mechanical properties.

Optimizing support performances of bolt reaming and anchoring in a coal drift

In current practice of bolt reaming and anchoring of roadways in soft coal and rock mass,resin cartridges bend easily under the strong pushing and stirring of bolts,and the resin accumulates in the bolt-reamed area and does not participate in the stirring.As a result,bolts encounter high drilling resistance and cannot reach the bottom of drillholes.The effective anchorage length is far less than the actual anchorage length.Bolts are not centered,and the shear is misaligned at the joint surface in the reaming area,which leads to cracking of the whole anchoring solid and large shear deformation of bolts.This study systematically analyzes the characteristics of roadway bolt reaming and anchoring.The influences of resin stirring force,bolt pull-out force,and reamingeanchoring solid strength on reamingeanchoring performance were analyzed theoretically.The main purpose is to develop a device that enhances reaming and anchoring.The mechanism through which the device strengthens the reamingeanchoring solid was analyzed theoretically.Numerical simulation and experiments were carried out to verify the improved performance of the small-pore reaming and anchoring using the proposed technology.The results showed that the stirring migration rate of the resin cartridge is greatly improved by adding the device to bolts.The reaction rate of the anchoring mixture,stirring pressure,pull-out force of the reaming and anchoring system,bolt concentricity,and shear and compressive strengths of the anchoring solid are also enhanced in the reaming area.This ensures that the resin cartridge in the reaming area is completely stirred,which greatly improves the shear resistance of the reamingeanchoring solid.Meanwhile,the drilling performance,torsional force,and stirring efficiency of bolts are maximized and prevail over those of conventional bolts.

Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Role of End-ring Configuration in Shaping IE4 Induction Motor Performance

The performance characteristics,particularly the starting performance of direct line-fed induction motors,which are mainly influenced by the design of the rotor,are crucial considerations for end-users.It is quite a challenging issue for motor manufacturers to enhance the starting performance of existing mass-produced motors with minimal modifications and expenses.In this paper,a simple and cost-effective method to improve the starting performance of a commercial squirrel-cage induction motor(SCIM)is proposed.The influence of geometric parameters of the end-ring on the performance characteristics,including starting(locked rotor)torque,pull-up and break down torque,starting current,rotor electric parameters,current density,power losses,and efficiency have been comprehensively investigated.It has been revealed that among the other end-ring design parameters,the ring thickness has a significant effect on the performance characteristics.An optimal end-ring thickness is determined,and its performance characteristics have been compared to those of its initial counterpart.Numeric and parametric analyses have been conducted using a 2D time-stepping finite element method(FEM).The FEM results were validated using experimental measurements obtained from an 11 kW SCIM prototype.

Unveiling Organic Electrode Materials in Aqueous Zinc-Ion Batteries:From Structural Design to Electrochemical Performance

Aqueous zinc-ion batteries(AZIBs)are one of the most compelling alternatives of lithium-ion batteries due to their inherent safety and economics viability.In response to the growing demand for green and sustainable energy storage solutions,organic electrodes with the scalability from inexpensive starting materials and potential for biodegradation after use have become a prominent choice for AZIBs.Despite gratifying progresses of organic molecules with electrochemical performance in AZIBs,the research is still in infancy and hampered by certain issues due to the underlying complex electrochemistry.Strategies for designing organic electrode materials for AZIBs with high specific capacity and long cycling life are discussed in detail in this review.Specifically,we put emphasis on the unique electrochemistry of different redox-active structures to provide in-depth understanding of their working mechanisms.In addition,we highlight the importance of molecular size/dimension regarding their profound impact on electrochemical performances.Finally,challenges and perspectives are discussed from the developing point of view for future AZIBs.We hope to provide a valuable evaluation on organic electrode materials for AZIBs in our context and give inspiration for the rational design of high-performance AZIBs.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

Instructional Planning Among Teachers in Public Secondary Schools in Kenya： Factors That Influence Performance in Business Studies

Instructional planning gives teachers control over teaching/learning process and assures learning achievement. However, instructional planning and the linkage to learning achievement remain deficient in literature. This study assessed factors influencing teachers＇ decision to plan lessons, and effect of lesson planning on learning achievement. Primary data were obtained from 341 teachers of business studies. Bivariate analysis obtained cross-tabulations with Chisquare （χ2） and One-way Analysis of Variance （ANOVA）; while multivariate analysis obtained β coefficients and odds ratios. The study found that average workload accounted for the highest variance in the availability of lesson plans at 8.5%, suggesting that reducing workload is likely to increase the proportion of those planning their teaching by up to 8.5%, followed by professional experience （7.6%）, lesson plan inspection frequency （6.9%）, professional training （5.9%）, administrative duties （5.8%）, and teacher motivation （4.7%）. The adjusted regression model explained 46.5% of variance in availability of lesson plans. The study recommends： higher budgetary allocation for Teachers＇ Service Commission to hire more teachers; school boards to generate supplementary resources and hire trained teachers; regular spot checks on lesson plans; and appropriate motivation for teachers.

Optimum Profiles of Endwall Contouring for Enhanced Net Heat Flux Reduction and Aerodynamic Performance

Successfully utilized non-axisymmetric endwalls to enhance turbine efficiencies(aerodynamic and turbine inlet temperatures)by controlling the characteristics of the secondary flow in a blade passage.This is accomplished by steady-state numerical hydrodynamics and deep knowledge of the field of flow.Because of the interaction between mainstream and purge flow contributing supplementary losses in the stage,non-axisymmetric endwalls are highly susceptible to the inception of purge flow exit compared to the flat and any advantage rapidly vanishes.The conclusions reveal that the supreme endwall pattern could yield a lowering of the gross pressure loss at the design stage and is related to the size of the top-loss location being productively lowered.This has led to diminished global thermal exchange lowered in the passage of the vane alone.The reverse flow adjacent to the suction side corner of the endwall is migrated farther from the vane surface,as the deviated pressure spread on the endwall accelerates the flow and progresses the reverse flow core still downstream.The depleted association between the tornado-like vortex and the corner vortex adjacent to the suction side corner of the endwall is the dominant mechanism of control in the contoured end wall.In this publication,we show that the non-axisymmetric endwall contouring by selective numerical shape change method at most prominent locations is advantageous in lowering the thermal load in turbines to augment the net heat flux reduction as well as the aerodynamic performance using multi-objective optimization.

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.

Influence of the Nature of the Incoming Sludge on the Performance of a Vertical Flow Reed Beds in Dakar-Senegal

This work investigates the influence of the type sludge on drainage, plant development, purification performances and biosolids quality. Drainage properties were measured through the frequency of clogging, the percentage of leachate recovered and the dryness of accumulated sludge. Plant development was measured through the density, the height and the stem diameter. Purification performance was evaluated from the reduction rate. Biosolids quality was measured after 3 months of maturation. The results show that the clogging frequencies were 9.5%;0% and 3.7%;the volume of leachate recovered was 42.2%;20.4% and 24.7% and, the dryness was 33.4%;61.1% and 52.4% for FS-ST, FS-STT and SS respectively. Plants densities were about, with densities 197.1, 171.3 and 178.3 plants/m2 in beds fed respectively with FS-ST, FS-STT and SS. Despite the high removal rates, the concentrations of pollutants in the leachates are above the Senegalese standard NS 05-061 for discharge into the environment. The biosolids are all mature with C/N and NH4+/NO3?ratios lower than 12 and 1 respectively. The biosolids are also rich in organic and mineral elements. The concentrations of Ascaris eggs are higher than the WHO recommendations. These biosolids should be stored for additional time or composted.

Selection of media tools for community planning:A study from the perspective of communicative planning

In community planning,due to the lack of evidence regarding the selection of media tools,this study examines how a common but differentiated ideal speech situation can be created as well as how more appropriate media tools can be defined and selected in the community planning process.First,this study describes the concept and theoretical basis of media used in community planning from the perspectives of the multiple effects of media evolution on communicative planning.Second,the classification criteria and typical characteristics of media tools used to support community planning are clarified from three dimensions:acceptability,cost effectiveness,and applicability.Third,strategies for applying media tools in the four phases of communicative planning-namely,state analysis,problem identification,contradictory solution and optimization-are described.Finally,trends in the development of media tools for community planning are explored in terms of multistakeholder engagement,supporting scientific decision-making and multiple-type media integration.The results provide a reference for developing more inclusive,effective,and appropriate media tools for enhancing decision-making capacity and modernizing governance in community planning and policy-making processes.

Atomic-resolution Interfacial Microstructure and Thermo-electro-magnetic Energy Conversion Performance of Gd/Bi_(0.5)Sb_(1.5)Te_(3)Composites

Thermo-electro-magnetic materials with simultaneously large magnetocaloric(MC)and thermoelectric(TE)effects are the core part for designing TE/MC all-solid-state cooling devices.Compositing MC phase with TE material is an effective approach.However,the elemental diffusion and chemical reaction occurring at the two-phase interfaces could significantly impair the cooling performance.Herein,Gd/Bi_(0.5)Sb_(1.5)Te_(3)(Gd/BST)composites were prepared by a low-temperature high-pressure spark plasma sintering method with an aim to control the extent of interfacial reaction.The reaction of Gd with the diffusive Te and the formation of GdTe nanocrystals were identified at the Gd/BST interfaces by the atomic-resolution microscope.The formed Bi’_(Te)antisite defects and enhanced{000 l}preferential orientation in BST are responsible for the increased carrier concentration and mobility,which leads to optimized electrical properties.The heterogeneous interface phases,along with antisite defects,favor the phonon scattering enhancement and lattice thermal conductivity suppression.The optimized composite sintered at 693 K exhibited a maximum ZT of 1.27 at 300 K.Furthermore,the well-controlled interfacial reaction has a slight impact on the magnetic properties of Gd and a high magnetic entropy change is retained in the composites.This work provides a universal approach to fabricating thermo-electro-magnetic materials with excellent MC and TE properties.