ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.

A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

Seismic performance evaluation of VCFPB isolated storage tank using real-time hybrid simulation

Variable curvature friction pendulum bearings(VCFPB)effectively reduce the dynamic response of storage tanks induced by earthquakes.Shaking table testing is used to assess the seismic performance of VCFPB isolated storage tanks.However,the vertical pressure and friction coefficient of the scaled VCFPB in the shaking table tests cannot match the equivalent values of these parameters in the prototype.To avoid this drawback,a real-time hybrid simulation(RTHS)test was developed.Using RTHS testing,a 1/8 scaled tank isolated by VCFPB was tested.The experimental results showed that the displacement dynamic magnification factor of VCFPB,peak reduction factors of the acceleration,shear force,and overturning moment at bottom of the tank,were negative exponential functions of the ratio of peak ground acceleration(PGA)and friction coefficient.The peak reduction factors of displacement,acceleration,force and overturning moment,which were obtained from the experimental results,are compared with those calculated by the Housner model.It can be concluded that the Housner model is applicable in estimation of the acceleration,shear force,and overturning moment of liquid storage tank,but not for the sliding displacement of VCFPBs.

Performance evaluation of near real-time condition monitoring in haul trucks

Strategic maintenance plays a key role in ensuring high availability and utilization of the haul trucks,and as equipment began to grow more complex towards the end of the 20th century,there was a need for a proactive maintenance strategy,which led to the development of condition-based maintenance.Realtime condition monitoring(RTCM)is the ability to perform condition monitoring in real-time and has the ability to alert maintenance and operations of abnormal conditions.These alarms can be used as an indication leading to a problem,and if a suitable corrective action is initiated in time,it could result in significant savings of equipment downtime and repair costs.This study aims to compare some maintenance performance indicators prior to and after implementation of RTCM strategy at a mine site using some tests of statistical significance.The study also indicated the presence of seasonality in the data,and thus the data was deseasonalized and detrended prior to being subjected to the statistical tests.Finally,the results indicated that RTCM strategy has proven to be successful in improving the availability for some of the failure categories chosen in this study.

Performance analysis model for real-time Ethernet-based computer numerical control system

In order to optimize the embedded system implementation for Ethernet-based computer numerical control （CNC） system, it is very necessary to establish the performance analysis model and further adopt the codesign method from the control, communication and computing perspectives. On the basis of analyzing real-time Ethemet, system architecture, time characteristic parameters of control-loop ere, a performance analysis model for real-time Ethemet-based CNC system was proposed, which is able to include the timing effects caused by the implementation platform in the simulation. The key for establishing the model is accomplished by designing the error analysis module and the controller nodes. Under the restraint of CPU resource and communication bandwidth, the experiment with a case study was conducted, and the results show that if the deadline miss ratio of data packets is 0.2%, then the percentage error is 1.105%. The proposed model can be used at several stages of CNC system development.

Optimizing Real-Time Performance of 3D Virtual Mining Environment with MultiGen Creator

System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a virtual mining system were discussed: optimizing 3D models to keep the polygon number in VR system within target hardware's processing ability; optimizing texture database to save texture memory with perfect visual effect; optimizing database hierarchy structure to accelerate model retrieval; and optimizing LOD hierarchy structure to speed up rendering.

Real-time performance of periodic data transmission in EPA industrial Ethernet

To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By analyzing information transmission regularity and EPA deterministic scheduling mechanism,periodic messages were categorized as different modes according to their entering-queue time.The scheduling characteristics and delivery time of each mode and their interacting relations were studied,during which the models of real-time performance of periodic information transmission in EPA system were established.On this basis,an experimental platform is developed to test the delivery time of periodic messages transmission in EPA system.According to the analysis and the experiment,the main factors that limit the real-time performance of EPA periodic data transmission and the improvement methods were proposed.

Probabilistic Automata-Based Method for Enhancing Performance of Deep Reinforcement Learning Systems

Deep reinforcement learning(DRL) has demonstrated significant potential in industrial manufacturing domains such as workshop scheduling and energy system management.However, due to the model's inherent uncertainty, rigorous validation is requisite for its application in real-world tasks. Specific tests may reveal inadequacies in the performance of pre-trained DRL models, while the “black-box” nature of DRL poses a challenge for testing model behavior. We propose a novel performance improvement framework based on probabilistic automata,which aims to proactively identify and correct critical vulnerabilities of DRL systems, so that the performance of DRL models in real tasks can be improved with minimal model modifications.First, a probabilistic automaton is constructed from the historical trajectory of the DRL system by abstracting the state to generate probabilistic decision-making units(PDMUs), and a reverse breadth-first search(BFS) method is used to identify the key PDMU-action pairs that have the greatest impact on adverse outcomes. This process relies only on the state-action sequence and final result of each trajectory. Then, under the key PDMU, we search for the new action that has the greatest impact on favorable results. Finally, the key PDMU, undesirable action and new action are encapsulated as monitors to guide the DRL system to obtain more favorable results through real-time monitoring and correction mechanisms. Evaluations in two standard reinforcement learning environments and three actual job scheduling scenarios confirmed the effectiveness of the method, providing certain guarantees for the deployment of DRL models in real-world applications.

Performance Evaluation of Multiple Unmanned Aerial Vehicles Operating in General Regime with Shortage of Maintenance Facilities

We consider a real-world problem of military intelligence unit equipped with multiple identical unmanned aerial vehicles (UAV) responsible for several regions (with requests of real-time jobs arriving from independent sources). We suppose that there are no ample maintenance facilities, allowing simultaneous treatment of all vehicles if necessary. Under certain assumptions, these real-time systems can be treated using a queueing theory methodology and/or as Markov chains. We show how to compute steady-state probabilities of these systems, their performance effectiveness, and various performance parameters (for exponentially distributed service and maintenance times of UAVs, as well as tasks duration and their arrival pattern).

Performance verification and comparison of TianLong automatic hypersensitive hepatitis B virus DNA quantification system with Roche CAP/CTM system

AIM To investigate and compare the analytical and clinical performance of Tian Long automatic hypersensitive hepatitis B virus(HBV) DNA quantification system and Roche CAP/CTM system.METHODS Two hundred blood samples for HBV DNA testing, HBV-DNA negative samples and high-titer HBV-DNA mixture samples were collected and prepared. National standard materials for serum HBV and a worldwide HBV DNA panel were employed for performance verification. The analytical performance, such as limit of detection, limit of quantification, accuracy, precision, reproducibility, linearity, genotype coverage and cross-contamination, was determined using the Tian Long automatic hypersensitive HBV DNA quantification system(TL system). Correlation and Bland-Altman plot analyses were carried out to compare the clinical performance of the TL system assay and the CAP/CTM system. RESULTS The detection limit of the TL system was 10 IU/m L, and its limit of quantification was 30 IU/m L. The differences between the expected and tested concentrations of the national standards were less than ± 0.4 Log10 IU/m L, which showed high accuracy of the system. Results of the precision, reproducibility and linearity tests showed that the multiple test coefficient of variation(CV) of the same sample was less than 5% for 102-106 IU/m L; and for 30-108 IU/m L, the linear correlation coefficient r2 = 0.99. The TL system detected HBV DNA(A-H) genotypes and there was no cross-contamination during the "checkerboard" test. When compared with the CAP/CTM assay, the two assays showed 100% consistency in both negative and positive sample results(15 negative samples and 185 positive samples). No statistical differences between the two assays in the HBV DNA quantification values were observed(P > 0.05). Correlation analysis indicated a significant correlation between the two assays, r2 = 0.9774. The Bland-Altman plot analysis showed that 98.9% of the positive data were within the 95% acceptable range, and the maximum difference was-0.49.CONCLUSION The TL system has good analytical performance, and exhibits good agreement with the CAP/CTM system in clinical performance.

Real-time hybrid simulation of structures equipped with viscoelastic-plastic dampers using a user-programmable computational platform

A user-programmable computational/control platform was developed at the University of Toronto that offers real-time hybrid simulation （RTHS） capabilities. The platform was verified previously using several linear physical substructures. The study presented in this paper is focused on further validating the RTHS platform using a nonlinear viscoelastic-plastic damper that has displacement, frequency and temperature-dependent properties. The validation study includes damper component characterization tests, as well as RTHS of a series of single-degree-of-freedom （SDOF） systems equipped with viscoelastic-plastic dampers that represent different structural designs. From the component characterization tests, it was found that for a wide range of excitation frequencies and friction slip loads, the tracking errors are comparable to the errors in RTHS of linear spring systems. The hybrid SDOF results are compared to an independently validated thermal- mechanical viscoelastic model to further validate the ability for the platform to test nonlinear systems. After the validation, as an application study, nonlinear SDOF hybrid tests were used to develop performance spectra to predict the response of structures equipped with damping systems that are more challenging to model analytically. The use of the experimental performance spectra is illustrated by comparing the predicted response to the hybrid test response of 2DOF systems equipped with viscoelastic-plastic dampers.

REAL-TIME SOFTWARE SYSTEM FOR PRODUCTION PROCESS SUPERVISION

The real-time software system for production process supervision is a inte-gral system,including on-line function subsystem for supervision and off-line auxiliarysubsystem for development and diagnosis.This paper introduces a real-time software sys-tem which has been used in a power station for monitoring a large capacity thermal gener-ating unit.The subsystems,environment,performance and development of the system areexplained,and the common problems about real-time software system are described.

Design of Intelligent Network Performance Analysis & Forecast Support System

A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.

Multiserver Multichannel Real-Time System with Limited Maintenance Facilities under Maximum Load

We consider a multi server and multichannel real-time system with identical servers (e.g. unmanned aerial vehicles, machine controllers, etc.) that provide services for requests of real-time jobs arriving via several different channels (e.g. surveillance regions, assembly lines, etc.) working under maximum load regime. Each channel has its own constant numbers of jobs inside at any instant. Each channel has its own specifications, and therefore different kinds of equipment and inventory are needed to serve different channels. There is a limited number of identical maintenance teams (less than the total number of servers in the system). We compute analytically steady- state probabilities of this system, its availability, loss penalty function and other performance characteristics, when both service and maintenance times are exponentially distributed.

Real-time predictions of the 2023–2024 climate conditions in the tropical Pacific using a purely data-driven Transformer model

Following triple La Nina events during 2020–2022,the future evolution of climate conditions over the tropical Pacific has been a focused interest in ENSO-related communities.Observations and modeling studies indicate that an El Nino event is occurring in 2023;however,large uncertainties remain in terms of its detailed evolution,and the factors affecting its resultant amplitude remain to be understood.Here,a novel deep learning-based Transformer model is adopted to make real-time predictions for the 2023–2024 climate conditions in the tropical Pacific.Several key fields vital to the El Nino and Southern Oscillation(ENSO)in the tropical Pacific are collectively and simultaneously utilized in model training and in making predictions;therefore,this purely data-driven model is configured in both training and predicting procedures such that the coupled ocean-atmosphere interactions are adequately represented.Also similar to dynamic models,the prediction procedure is executed in a rolling manner to allow ocean-atmosphere anomaly exchanges month by month;the related key fields during multi-month time intervals(TIs)prior to prediction target months are taken as input predictors,serving as initial conditions to precondition the future evolution more effectively.Real-time predictions indicate that the climate conditions in the tropical Pacific are surely to develop into an El Nino state in late 2023.Furthermore,sensitivity experiments are conducted to examine how prediction skills are affected by the input predictor specifications,including TIs during which information on initial conditions is retained for making predictions.A comparison with other dynamic coupled models is also made to demonstrate the prediction performance for the 2023–2024 El Nino event.

农超对接模式下农产品冷链物流协同绩效的评价

基于BSC策略,结合专家咨询建议,构建了农超对接模式下农产品冷链物流协同绩效评价指标,然后采用层次分析法对指标测算权重,利用模糊综合评价法对农超对接模式下农产品冷链物流的协同绩效进行了综合评价。研究表明,农超对接模式下农产品冷链物流协同绩效的成本协同程度、内部业务协同程度、协同管理能力评价分级标准为"一般",服务质量协同程度评价分级标准为"较好"。因此,要提升农超对接模式下农产品冷链物流协同绩效,寻求政府支持,加强政企合作,降低运营成本,加强农产品冷链物流标准的完善与执行,加强农户、超市等销售终端和农产品冷链物流企业组织的协调性,完善农产品冷链信息系统,实现共赢。

Real-time and reliability analysis of time-triggered CAN-bus

Real-time performance and reliability are two most important issues in applications of time-triggered controller area network （CAN） bus systems at present. A scheduling matrix of time-triggered CAN-bus system is established using average-loading algorithm. Periodic messages are guaranteed to transmit without delay by distributing independent transmission windows within the system matrix. Considering the traditional CAN-bus transmission mechanism and the time-triggered feature, an algorithm is improved to calculate the worst-case delay of event-triggered messages in time-triggered CAN-bus systems. The failure probability is calculated for event-triggered messages whose worst-case delay exceeds their deadlines. Different levels of redundant structures of CAN-bus circuits are analyzed and the maintenance management is proposed to improve the system reliability. Finally, the reliabilities of different structures are calculated and the influences of maintenance on the system reliability are analyzed.

The IOCAS intermediate coupled model(IOCAS ICM) and its real-time predictions of the 2015–2016 El Nio event

The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the inten- sity forecast and are strongly model dependent. An intermediate coupled model （ICM） is used at the Institute of Oceanology, Chinese Academy of Sciences （IOCAS）, named the IOCAS ICM, to predict the sea surface temper- ature （SST） evolution in the tropical Pacific during the 2015-2016 E! Nifio event. One unique feature of the IOCAS ICM is the way in which the temperature of subsurface water entrained in the mixed layer （Te） is parameterized. Observed SST anomalies are only field that is utilized to initialize the coupled prediction using the IOCAS ICM. Examples are given of the model＇s ability to predict the SST conditions in a real-time manner. As is commonly evident in E1 Nifio- Southern Oscillation predictions using coupled models, large discrepancies occur between the observed and pre- dicted SST anomalies in spring 2015. Starting from early summer 2015, the model can realistically predict warming conditions. Thereafter, good predictions can be made through the summer and fall seasons of 2015. A transition to normal and cold conditions is predictecl to occur in rote spring 2016. Comparisons with other model predictions are made and factors influencing the prediction performance of the IOCAS ICM are also discussed.

MIPS-Ⅲ架构的数控系统实时性能评估方法研究

为了评估和优化基于国产MIPS处理器的PC型数控系统的实时性和稳定性,结合数控系统和实时系统的特点,从事件延迟和周期抖动两个影响实时系统时间特性的关键因素出发,提出一套评估基于MIPS的PC型数控系统实时性能和稳定性能的关键指标分析方法 CNC-KDE(CNC-Key Department Evaluation),该方法包含了评估的关键指标选取、关键指标实验数据采集方法、关键指标实验数据的数理统计分析方法.最后根据关键指标分析结果对数控系统的实时性能和稳定性能进行综合的评估.文中还介绍了该方法应用于原型机数控系统的评估实验,实验结果表明CNC-KDE方法能对基于MIPS架构的PC型数控系统的实时性能和稳定性可以进行准确有效的分析和评估.

Implementation System of Human Eye Tracking Algorithm Based on FPGA

With the high-speed development of transportation industry,highway traffic safety has become a considerable problem.Meanwhile,with the development of embedded system and hardware chip,in recent years,human eye detection eye tracking and positioning technology have been more and more widely used in man-machine interaction,security access control and visual detection.In this paper,the high parallelism of FPGA was utilized to realize an elliptical approximate real-time human eye tracking system,which was achieved by the series register structure and random sample consensus(RANSAC),thus improving the speed of image processing without using external memory.Because eye images acquired by the camera often generate a lot of noises due to uneven light and dark background,the preprocessing technologies such as color conversion,image filtering,histogram modification and image sharpening were adopted.In terms of feature extraction of images,the eye tracking algorithm in this paper adopted seven-section rectangular eye tracking characteristic method,which increased a section between the mouth and the nose on the basis of the traditional six-section method,so its recognition accuracy is much higher.It is convenient for the realization of hardware parallel system in FPGA.Finally,aiming at the accuracy and real-time performance of the design system,a more comprehensive simulation test was carried out.The human eye tracking system was verified on DE2-115 multimedia development platform,and the performance of VGA(resolution:640×480)images of 8-bit grayscale was tested.The results showed that the detection speed of this system was about 47 frames per second under the condition that the detection rate of human face(front face,no inclination)was 93%,which reached the real-time detection level.Additionally,the accuracy of eye tracking based on FPGA system was more than 95%,and it has achieved ideal results in real-time performance and robustness.