非完整轮式移动机器人运动控制系统的设计与实现

通过对非完整轮式移动机器人运动学模型的分析，以Elmo HARmonica伺服驱动控制器为核心，设计了轮式移动机器人的运动控制系统。基于Visual C 和OpenGL平台开发了轮式移动机器人轨迹跟踪仿真系统，并进行了轨迹跟踪的仿真试验，取得了满意的控制效果。实验结果表明了运动控制系统设计的有效性。     

基于模糊预测控制的路径跟踪控制研究

在构建与分析移动机器人运动学模型基础上,研究了基于模糊预测控制的移动机器人路径跟踪控制方法。充分利用模糊控制和预测控制优点,改进了传统模糊控制算法,提高了移动机器人路径跟踪的快速性和平稳性。仿真实验表明,机器人的仿真轨迹和参数表现良好。     

基于改进型DAISY的稀疏三维地图构建的算法

局部三维地图构建与移动轨迹跟踪在无人机导航、移动机器人和AR等众多领域有着非常重要的作用.本文采用改进型DAISY特征描述符对视频图像序列进行特征匹配跟踪,再利用对极约束求解基础矩阵,结合对极几何与射影几何关系得到相机参数与三维空间点坐标,最后利用增量BA优化三维稀疏地图和相机移动轨迹.实验表明本算法的特征点正确匹配率、三维点重建精度与完整度均有提高,能够输出清晰的相机移动轨迹和三维稀疏地图.     

基于卡尔曼预测的轨迹片段关联目标跟踪算法

利用卡尔曼算法对运动目标跟踪展开研究,提出了一种基于卡尔曼预测的轨迹片段关联目标跟踪算法。首先利用卡尔曼预测缩小搜索区域,对检测结果进行匹配关联,生成可信的短轨迹片段;然后对每个轨迹片段通过卡尔曼预测迭代关联,形成单个目标的跟踪轨迹集合。实验证明该方法可有效提高轨迹片段关联跟踪算法效率,解决目标相互遮挡问题,实现对目标的稳定跟踪。     

不确定机器人自适应鲁棒迭代学习控制研究

针对未知时变参数的不确定性和未知外部干扰的机械手轨迹跟踪问题,提出了一种具有抗扰能力的自适应鲁棒迭代学习控制算法。该算法引入鲁棒项,实现不确定机器人动力学系统鲁棒控制;结合系统模型的不确定性和干扰不重复,对系统进行相关数学理论分析,运用泰勒公式和Lyapunov函数分别进行线性化及稳定性分析;以二连杆机械手为例,基于MATLAB软件进行仿真,结果表明：改进后的算法跟踪效果好,收敛误差速度快。该智能控制算法可实现对不确定机器人系统轨迹精确跟踪,并加快跟踪误差的收敛速度。     

基于激光雷达的Bobac机器人S型障碍物避障轨迹规划研究

文章基于Bobac移动机器人的室内S型障碍物避障轨迹规划设计研究，采用激光雷达传感器与双轮控制相结合方式，实现S型障碍物避障轨迹规划，并实现精准定位，达到避障目的。论文主要以Bobac智能移动机器人平台为研究对象，分析智能移动机器人中里程信息不精确的问题，并基于网格Fast SLAM方法环境模型的建立实现提高计算效率以及定位精度。通过对激光雷达精度与距离关系的深入分析，提出了在精准区与模糊区内建立一种S型障碍物避障方法，引入运动模型和激光雷达传感器测量误差模型进行实时修正。文章采用自适应控制方法在实时估计Bobac机器人与障碍物距离的同时，控制移动机器人渐进跟踪期望轨迹，证明了双轮实时控制与激光雷达配合的稳定性。实验证明，相较于传统的激光雷达避撞方法，本研究所提出方法可以有效地提高在S型障碍物内避障运动。     

刚性机器人全局高速非奇异终端滑模控制

针对刚性机器人有限时间鲁棒控制问题,为了提高控制性能,提出全局高速非奇异终端滑模及相应的滑模控制策略,并将新的滑模控制策略应用到刚性机器人轨迹跟踪控制中。该文所提出的全局高速非奇异终端滑模不仅具有非奇异快速终端滑模所不具备的全局高速收敛特性,而且可以提供全局非奇异性。实例仿真研究结果表明,该控制策略可以实现对期望轨迹的全局高速有限时间非奇异鲁棒跟踪,有效地提高了刚性机器人控制性能。     

基于迭代控制的两自由度移动小车路径跟踪控制

基于迭代控制的两自由度移动小车路径跟踪控制主要是研究小车在两自由度情况下的路径跟踪情况.利用迭代学习控制算法使小车的跟踪误差以最快的速度达到零,从而达到理想的跟踪效果.仿真结果表明,迭代学习控制具有很好的跟踪效果.     

基于轨迹提取的舞蹈基础训练动作跟踪方法

为提出基于轨迹提取的舞蹈基础训练动作跟踪方法,降低复杂背景对跟踪效果的影响,助力舞蹈教学工作顺利开展,本文以舞蹈基础训练动作图像为输入构建FasterR-CNN模型,模型输入层依据各个舞蹈基础训练动作特点进行分类,并抽取每个分类的图像;将其输入到识别层获取舞蹈基础训练动作的分类与定位结果;关联层利用最小参照点投映间隔长度关联多幅图像的舞蹈基础训练动作定位结果,获得动作持续运动参照点位;参照点位经过拟合层拟合后,完成舞蹈基础训练动作轨迹提取;通过傅里叶变换将提取轨迹的跟踪过程视为相应函数的优化过程,实现舞蹈基础训练动作轨迹跟踪。实验结果表明,该方法可以准确地拟合出完整的舞蹈基础训练动作轨迹,同时可有效跟踪舞蹈基础训练动作的多个点位,未出现点位缺失或偏移情况,且动作跟踪完整度受背景复杂度影响较小。     

四旋翼无人机高度控制——基于CNF与自适应非光滑控制

针对受限环境下四旋翼无人飞行器在参数不确定及外部扰动影响下的高性能高度控制问题,设计一种基于复合非线性反馈（CNF）和自适应非光滑轨迹跟踪控制的高度控制方法。通过四旋翼无人飞行器的垂直通道动力学模型分析和变换,将高度轨迹规划问题转换为输入受限的线性系统控制问题,设计CNF控制器实现轨迹生成;建立参数不确定及外部扰动影响下的垂直通道动力学模型,设计一种自适应非光滑轨迹跟踪控制器,并理论证明了闭环系统稳定性。最后,通过仿真实验验证所提出方法的有效性。结果表明,所设计方法能够有效提高参数不确定及外部扰动下的高度控制品质,且简单实用。     

线性时滞系统开闭环PID型迭代学习控制

针对线性时滞系统讨论了开闭环PID型迭代学习控制算法。对于初始状态函数渐近重复的情形,给出了这类系统的极限轨迹和迭代输出收敛于该极限轨迹的较弱的充分条件。仿真结果表明,这种算法是有效的。同时,从仿真实例也可看出,在收敛速度方面,开闭环算法优于开环算法。     

线性离散系统的H∞开环迭代学习控制器设计

针对线性离散系统,研究了开环动态迭代学习控制律的设计问题.首先给出了闭环系统的收敛充分条件,然后把迭代控制转化为H∞设计问题,最后利用线性矩阵不等式（LMI）方法求解迭代学习控制器.通过仿真实例表明了设计方法的有效性.     

具有动态学习能力的分层进化粒子群优化算法

针对粒子群算法(PSO)在优化高维多极值问题时容易陷入局部极值的问题,结合分层进化与动态学习策略,提出一种具有动态学习能力的分层进化粒子群优化算法(DHEPSO).该算法首先根据粒子适应度值将粒子划分为不同层级,对不同层级粒子采取不同的进化策略,避免迭代后期种群多样性快速消失;然后根据粒子所属层级的不同动态调整粒子学习...     

The impact of AI and robotics on physical,social-emotional and intellectual learning outcomes: An integrated analytical framework

This qualitative study examines the use of artificial intelligence (AI) and robotics in learning designs from the perspective of learning sciences. The literature on the topic indicates that there is not enough research on including diverse learning outcomes in the designs for learning. Therefore, the purpose of this study was to understand how AI and robots impact physical, social-emotional and intellectual learning outcomes through the implementation of learning designs that are guided by selected design principles. In this study, the design-based research (DBR) methodology was employed for investigating learning in naturalistic contexts. The intervention was implemented in a primary school in which learners used educational robots. The main findings reveal that the development of an integrated analytical framework, which considers a broader spectrum of human potential, allows for analyzing students’ learning outcomes in a more integral, inclusive and balanced way. This, in turn, promotes students’ learning by using AI and robots. Another finding reveals that the impact of using AI and robotics on learning designs is reflected in learners’ personal trajectories having different pathways and paces. Finally, the lessons learned and the challenges to be overcome are summarized, and recommendations are made for future research for the enhancement of learning experiences that use AI and robotics.     

国外教育机器人辅助语言学习研究:认知激活与情感驱动

本文系统分析了国外教育机器人辅助语言学习的研究,发现其内容涵盖两个方面.第一是对参与者语言学习结果的认知激活,第二是侧重于对情感方面驱动作用研究.前者的研究以词汇学习为主,还包括如阅读、口语和语法等其他技能;后者关注教育机器人对学习动机的积极影响、教育机器人辅助语言学习的新颖性效应和教育机器人社会行为的复杂性.目前我国...     

中频发电机变频电源的自抗扰技术研究

针对目前中频发电机在满载时,采用开环控制运行下,系统抗干扰能力较差的问题,提出了一种基于自抗扰控制器（ADRC）的逆变器控制方法。自抗扰控制器完全独立于被控对象的具体数学模型,把系统所有不确定因素与外部扰动归结于系统总扰动,通过扩张状态观测器（ESO）对扰动进行观测,然后利用非线性状态误差反馈律（NLSEF）进行补偿。仿真和实验结果表明,所设计的自抗扰控制器能有效抑制负载及永磁发电机的干扰,具有良好的动态特性及较强的鲁棒性。     

Children’s Cognitive and Behavioral Reactions to an Autonomous Versus Controlled Social Robot Dog

Research Findings: Interactive technology has become ubiquitous in young children’s lives, but little is known about how children incorporate such technologies into their intuitive biological theories. Here we explore how the manner in which technology is introduced to young children impacts their biological reasoning, moral regard, and prosocial behavior toward it. We asked 5- and 7-year-old children to interact with a robot dog that was described either as moving autonomously or as remote controlled. Compared with a controlled robot, the autonomous robot caused children to ascribe higher emotional and physical sentience to the robot, to reference the robot as having desires and physiological states, and to reference moral concerns as applying to the robot. Children who owned a dog at home were more likely to behave prosocially toward the autonomous robot than those who did not. Practice or Policy: Recent work has begun to use robots as learning tools. Our results suggest that the manner in which robots are introduced to young children may differentially impact children’s learning. Presenting robots as autonomous agents may help promote children’s social-emotional development, whereas presenting robots as human controlled may help promote robots as purely cognitive educational tools.     

Adaptive swarm-based routing in communication networks

Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features,including adaptation,robustness and distributed,decentralized nature,which are well suited for routing in modern communication networks.This paper describes an adaptive swarm-based routing algorithm that increases convergence speed,reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum.Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.     

Adaptive swarm-based routing in communication networks

INTRODUCTION Communication network management ibecoming increasingly difficult due to thincreasing size, rapidly changing topology, ancomplexity of communication networks. Currenrouting algorithms cannot adequately tackle sucnetworks. Centralized algorithms have scalabilitproblems; static algorithms have trouble keepinup-to-date with network changes; and othedistributed and dynamic algorithms havoscillation and s…     

Digital Learning Playground: supporting authentic learning experiences in the classroom

This study proposes a platform to provide a near-authentic environment, context, and situation for task-based learning. The platform includes two projection screens (a vertical and a horizontal screen) combined for situated or authentic learning. The horizontal screen extends the vertical screen scene to form a space for learning activities and performance. The platform creates learning situations using robots as surrogates of students to accomplish real-life tasks. Kolb's four-stage experiential learning cyclical model was adopted in the learning design. A simple practice was developed to examine the effect on teaching children English as a foreign language. The results reveal that children could engage deeply and feel more enjoyment using the system. Moreover, as surrogates for students to imagine that they are accomplishing real-life missions, robots could be a vital element of authentic learning in future classrooms.