Adaptive Nonlinear PD Controller of Two-Wheeled Self-Balancing Robot with External Force

This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.

Design of Indoor Security Robot based on Robot Operating System

The design and implementation of indoor security robot can well integrate the two fields of indoor navigation and object detection, in order to achieve a more powerful robot system, the development of this project has certain theoretical research significance and practical application value. The project development is completed in ROS (Robot Operating System). The main tools or frameworks used include AMCL (Adaptive Monte Carlo Localization) package, SLAM (Simultaneous Localization and Mapping) algorithm, Darknet deep learning framework, YOLOv3 (You Only Look Once)algorithm, etc. The main development methods include odometer information fusion, coordinate transformation, localization and mapping, path planning, YOLOv3 model training, function package configuration and deployment. Indoor security robot has two main functions: first, it can complete real-time localization, mapping and navigation of indoor environment through sensors such as lidar and camera;Second, object detection is accomplished through USB camera. Through the detailed analysis and research of the functional design of the two modules, the expected function is finally realized, which can meet the daily use needs.

Amassing the Security:An Enhanced Authentication and Key Agreement Protocol for Remote Surgery in Healthcare Environment

The development of the Internet of Things has facilitated the rapid development of various industries.With the improvement in people’s living standards,people’s health requirements are steadily improving.However,owing to the scarcity of medical and health care resources in some areas,the demand for remote surgery has gradually increased.In this paper,we investigate remote surgery in the healthcare environment.Surgeons can operate robotic arms to perform remote surgery for patients,which substantially facilitates successful surgeries and saves lives.Recently,Kamil et al.proposed a secure protocol for surgery in the healthcare environment.However,after cryptanalyzing their protocol,we deduced that their protocols are vulnerable to temporary value disclosure and insider attacks.Therefore,we design an improved authentication and key agreement protocol for remote surgeries in the healthcare environment.Accordingly,we adopt the real or random(ROR)model and an automatic verification tool Proverif to verify the security of our protocol.Via security analysis and performance comparison,it is confirmed that our protocol is a relatively secure protocol.

Robotic Process Automation with New Future Trends

The invention concept of Robotic Process Automation (RPA) has emerged as a transformative technology that has revolved the local business processes by programming repetitive task and efficiency adjusting the operations. This research had focused on developing the RPA environment and its future features in order to elaborate on the projected policies based on its comprehensive experiences. The current and previous situations of industry are looking for IT solutions to fully scale their company Improve business flexibility, improve customer satisfaction, improve productivity, accuracy and reduce costs, quick scalability in RPA has currently appeared as an advance technology with exceptional performance. It emphasizes future trends and foresees the evolution of RPA by integrating artificial intelligence, learning of machine and cognitive automation into RPA frameworks. Moreover, it has analyzed the technical constraints, including the scalability, security issues and interoperability, while investigating regulatory and ethical considerations that are so important to the ethical utilization of RPA. By providing a comprehensive analysis of RPA with new future trends in this study, researcher’s ambitions to provide valuable insights the benefits of it on industrial performances from the gap observed so as to guide the strategic decision and future implementation of the RPA.

Motor Learning Based on the Cooperation of Cerebellum and Basal Ganglia for a Self-Balancing Two-Wheeled Robot

A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.

基于PLC+4G的病案库房远程巡查机器人研发

研发一款远程视频巡查库房中病案霉变痕迹、虫害痕迹及库房渗水痕迹的机器人。机器人采用四轮行走形式,2个后轮由2台步进电机分别驱动。机器人上安装垂直升降丝杆,其滑块上安装水平伸缩丝杆,一台筒形病案检查摄像机安装在水平丝杆滑块上,2根丝杆均由步进电机驱动,另有2台360°球形摄像机保证机器人行走无盲区。设计用户手机端HMI,点击HMI上按钮,通过物联网-4G-4G网关数据链向机器人上的PLC发出指令,控制机器人把病案检查摄像机移动到检查位置。3台摄像机视频通过另一条4G-物联网数据链传到用户电脑屏幕显示。实验验证远程控制系统及信号传输数据链切实可行,可在电脑上远程视频察看库房病案存储状况,确保病案安全。

模块类网络安全产品的智能测试系统设计

为提高模块类网络安全产品的批量测试效率,降低人力成本及换线时间,开展了模块类网络安全产品的智能测试系统设计;通过对模块类网络安全产品的智能测试需求进行分析,采用将搭载图像传感器的工业机械手与基于PXI架构的测试系统相结合的技术路线,并对机械手控制技术和PXI总线测试平台设计技术进行了研究;创新设计了模块类网络安全产品的智能测试系统,对测试工艺流程进行优化与再造,实现了产品上下料、型号识别与柔性换线、智能装夹、批量测试、合格品与不合格品分拣等流程的一站式无人值守运转;经实际应用验证,智能测试系统的单日测试产能提升超过180%,单日人工工时减少93%以上,换线时间从平均70分钟减少到10分钟以内。

人工智能发展和安全并重的法治探究——以人形机器人为例

基于“大数据+高算力+强算法”的人形机器人,能够实现连贯高效的人—机—环境智能交互,可服务特种领域需求,助力智能制造,成为人类生活助手和情感伴侣。尽管人形机器人存在功能安全、网络安全、个人信息安全、数据安全、国家安全、违法“代理”、侵权、伦理等多种风险,但如果过度追求安全,就会扼杀创新而阻碍发展。发展是安全的基础,安全是发展的条件,应实现人工智能发展和安全并重。通过理性实施包容审慎监管,推动人形机器人在发展中规范、在规范中发展。科学合理地开展安全风险评估,将人形机器人风险控制在可接受的水平。完善数据安全认证、个人信息保护认证等第三方声誉评价机制,并分级分类推动人形机器人标准制定。应合理配置相关主体的责任,避免人形机器人的过度拟人化,防止陷入“人形机器人陷阱”。通过完善的伦理规范约束人工智能研发者,并为人形机器人“加载”道德,使其对人和环境友好。

机器人操作系统ROS安全性研究综述

机器人日益走进人们的日常生活,也受到了国内外越来越多的关注.机器人系统的一个重要特性是安全性,增强机器人系统的安全性可以保护机器人免受恶意攻击者的入侵.机器人操作系统的安全性是机器人系统安全性的重要组成部分.虽然近年来研究人员针对机器人操作系统的安全性做了许多研究工作,但遗憾的是,安全性目前还没有得到足够的重视.为了引起人们对机器人系统安全性更多的关注,同时帮助人们快速了解当前主流机器人操作系统ROS(robot operating system)的安全性解决方案,对ROS的安全性进行系统的调研和总结.一方面,深入分析ROS的安全特性,总结ROS中已知的安全问题.另一方面,对近年来ROS安全性相关的研究进行分类分析和概括总结,并从机密性、完整性和可用性这3个方面,对众多ROS的安全性解决方案进行比较.最后,对ROS安全性研究的前景进行展望.

虚假数据注入攻击下多机器人系统协同寻源

聚焦多机器人系统协同寻源问题,即通过驱使多个机器人相互协同寻找未知环境中物理信号放射源的位置.由于执行任务的机器人通常处于户外开放网络环境中,攻击者在网络中生成的虚假数据注入攻击容易导致多机器人系统寻源任务的失败.为在网络攻击情形下仍旧能够追寻到源点,提出一种基于弹性向量趋同的多机器人系统协同多维寻源方法.有别于现有文献在处理多维寻源时将向量分解成各个维度上的标量进而设计基于标量的弹性趋同协议,所提出的多维寻源方法不仅能够有效抵御虚假数据注入攻击完成寻源任务,而且其界定的安全区间相较于传统基于标量信息界定的安全区间更加严格和精准.在假设f-局部有界(f-locally bounded)虚假数据注入攻击模型下,理论分析给出正常机器人在所设计的控制协议下追寻到源点的充分必要条件.仿真结果表明,该方法在分布式多机器人系统协作寻源和抵抗恶意攻击方面具有优越性.

基于软件机器人的工控靶场应用软件行为模拟

工控靶场为开展工业控制系统(ICS)安全研究提供重要支撑。面向工控靶场关键任务之一的应用软件行为模拟,提出一种软件机器人方法以实现工控靶场应用软件行为的逼真模拟。考虑软件图形界面及软件内在显隐式规则,提出基于尺度不变特征变换(SIFT)图像相似度的软件菜单采集算法及混合状态机模型对应用软件行为进行建模。针对软件机器人的智能化问题,使用深度Q网络(DQN)算法驱动软件机器人对应用软件行为进行自主学习,同时结合多重经验回访和多重目标网络对DQN算法进行优化。实验结果表明:基于DQN的软件机器人能够对工控软件进行有效学习,且优化后的DQN算法自主学习效果更佳。

基于粒子群的多毫米波安防机器人环境感知方法

安防机器人常工作于昏暗、烟雾等环境,毫米波有探测这类环境的能力,但其点云是稀疏的,可将多毫米波的点云融合以提高环境感知的能力。点云融合时需要精确的结构参数,针对测量法获取结构参数存在误差的问题,在分析多毫米波点云坐标的基础上,利用粒子群算法对毫米波雷达结构参数进行搜索,并根据搜索结果进行点云融合以及环境地图的构建;同时提出稀疏点云地图的评价指标,对毫米波感知效果进行定量评价。利用安防机器人在昏暗环境下开展实验,结果表明与结构参数由测量法获取的多毫米波感知系统对比,点云数量有所增加,地图边界空洞数量平均减少55%,边界噪声率平均下降12.9%,物体点云离散度平均下降约0.06,中心位置的偏移量均有所减小。

一种基于ROS的分布式安防巡逻机器人系统

针对目前安防巡逻机器人系统中对机器人主控机负载能力要求较高的问题,设计一种基于机器人操作系统(robot operating system,ROS)的分布式安防巡逻机器人系统。将同时定位与建图(simultaneous localization and mapping,SLAM)节点以及视觉识别节点分布于局部ROS网络中的机器人主控机和远程监控端,SLAM方面采用gmapping算法实现动态环境中的地图构建以及机器人的定位;视觉识别方面采用TensorFlow深度学习框架,利用TensorFlow Object Detection API实现场景里多个物体的识别。结果表明,该系统为基于ROS的分布式安防巡逻机器人系统的设计提供了参考。

ROSIC: Enhancing secure and accessible robot control through open‐source instant messaging platforms

Ensuring secure communication and seamless accessibility remains a primary challenge in controlling robots remotely.The authors propose a novel approach that leverages open-source instant messaging platforms to overcome the complexities and reduce costs associated with implementing a secure and user-centred communication system for remote robot control named Robot Control System using Instant Communication(ROSIC).By leveraging features,such as real-time messaging,group chats,end-to-end encryption and cross-platform support inherent in the majority of instant messenger platforms,we have developed middleware that establishes a secure and efficient communication system over the Internet.By using instant messaging as the communi-cation interface between users and robots,ROSIC caters to non-technical users,making it easier for them to control robots.The architecture of ROSIC enables various scenarios for robot control,including one user controlling multiple robots,multiple users con-trolling one robot,multiple robots controlled by multiple users,and one user controlling one robot.Furthermore,ROSIC facilitates the interaction of multiple robots,enabling them to interoperate and function collaboratively as a swarm system by providing a unified communication platform that allows for seamless exchange of data and com-mands.Telegram was specifically chosen as the instant messaging platform by the authors due to its open-source nature,robust encryption,compatibility across multiple platforms and interactive communication capabilities through channels and groups.Notably,the ROSIC is designed to communicate effectively with robot operating system(ROS)-based robots to enhance our ability to control them remotely.

企业机器人渗透度与社保缴费水平——来自制造业上市公司的证据

机器人对劳动力市场的影响已延伸至社会保险领域,考察机器人渗透度对企业社保缴费水平的影响至关重要。研究发现:机器人渗透度的提高降低了企业的社保缴费水平。异质性分析发现,机器人渗透度对社保缴费水平的负向影响在劳动力密集程度更高、融资约束更强和非国有企业中更为显著。机制检验发现,企业机器人的应用通过要素替代效应、技术偏向效应和挤出效应降低了企业社保缴费的意愿和水平。因此,需要从制度设计出发来完善现行的社会保险制度,兼顾企业的经营效率与社会保险责任的承担,从而保障社会保险基金的可持续性。

结合改进YOLOv8n及SLAM的机器人自主巡检控制系统研究

本文提出了一种基于改进YOLOv8n及SLAM的室内安防机器人自主巡检控制系统方案。目标检测采用轻量化处理的YOLOv8n算法,使用GhostNet进行YOLOv8n的轻量级改进。达到降低计算量和内存消耗,同时提高目标检测速度的目的。改进后的YOLOv8n帧率相较于改进前速度提升50%,模型缩小为原来的63%,而识别的精确度仅下降5%左右。为提高机器人对未知环境的感知能力和自主性,使用了Cartographer算法。基于此算法,机器人可实现自主导航和地图构建,定位过程中估计值与实际值的横向偏差小于0.06 m;纵向偏差小于0.08 m;航向偏角小于16°。实验结果表明:该系统能够实现地图的精确构建以及目标火焰的快速检测,并实现实时预警。

具身智能的数据安全风险及刑法应对——以人形机器人的研发与应用为例

人工智能的具身化意味着人工智能产品由代码塑造的虚拟空间进入更为复杂的现实世界,具备强大的环境感知、认知交互、智能决策、行动控制能力,而这一切都依赖规模庞大、类型多样的数据处理活动作支撑,人形机器人研发与应用过程中也催生了数据控制安全风险和数据利用安全风险。刑法作为数据安全治理的重要手段,应当引入前置法确立的数据分类分级保护规则指导数据犯罪立法完善与司法认定,通过将过失泄露个人信息行为以及非法篡改、毁损、滥用个人信息行为犯罪化,全流程管控具身智能领域个人信息安全风险;通过增设非法持有重要数据罪和非法出售、提供重要数据罪并调适侵害重要数据行为的入罪标准,高强度防范具身智能领域重要数据安全风险。居于数据安全保证人地位的具身智能服务提供者是从源头防范和化解数据安全风险的第一责任主体,负有保护具身智能数据安全的作为义务,应依次判断作为可能性和结果回避可能性,合理确定具身智能服务提供者怠于履行数据安全保护义务时承担不作为刑事责任的边界。

冷轧机组钢卷拆捆机器人的应用研究

针对人工拆捆带作业劳动强度大、效率低、剪捆带时捆带弹出容易伤人等问题,提出让钢卷拆捆机器人代替人工从事钢卷拆捆带工作。机器人通过激光测距仪和超声波距离传感器的相互配合,经过机器人运动模型的参数计算,实现捆带自动识别和精确定位,再通过剪切装置和打卷退料装置,完成捆带的剪切及回收。该机器人的投入使用,可快速将捆带拆除,能耗少,速度快,现场工作稳定可靠,实现了钢卷打捆带的拆捆和回收的全部自动化作业,值得推广应用。

A DoS Attacks Detection Aglorithm Based on Snort-BASE for Robotic Arm Control Systems

In response to the frequent safety accidents of industrial robots, this paper designs and implements a safety detection system for robot control. It can perform real-time security detection of robot operations on industrial production lines to improve the security and reliability of robot control systems. This paper designs and implements a robot control system based Snort-BASE for real-time online detection of DoS attacks. The system uses a six-degree-of-freedom robotic arm as an example, uses Snort to record the network communication data of the robot arm control system in real time, and filters the network traffic through self-defined rules, and then uses the BASE analysis platform to achieve security analysis of the network traffic. The solution verifies the effectiveness of online real-time detection of attacks and visualisation of attack records by designing simulated robotic arm and real robotic arm attack experiments respectively, thus achieving the security of network communication of the robot remote control system.

财务机器人在饲料企业会计中的影响及对策研究

随着现代科学技术的进步,财务机器人的应用已深入会计领域,也使得会计行业智能化应用中取得了进一步突破,为饲料行业的发展做出了贡献。文章介绍了财务机器人在饲料企业会计中的优势,也明确了财务机器人在饲料企业会计应用中的不足并针对不足提出建议和意见,为饲料企业会计人员更好的应对人工智能时代和应用财务机器人奠定了基础。