一种用于接力赛的NAO机器人比赛系统设计

基于NAO机器人平台设计了一种机器人接力比赛系统,提出并试验了一种基于接力赛比赛规则的机器人控制系统。通过单目视觉控制NAO机器人识别并区分周围环境和接力赛赛场跑道;通过运动控制设计控制NAO机器人完成行走转弯等动作;利用Socket通信设计 NAO机器人之间的接力通信使机器人完成整个比赛流程。设计了逆运动学求解步态算法,使比赛系统具有稳定性及快速性。实验证明该比赛系统可行,且该系统在 “软银机器人杯”2018中国机器人技能大赛中获得一等奖。     

双足机器人NAO爬楼步态规划

双足机器人的爬楼梯性能是衡量其在复杂环境下行走能力的一项重要指标.本文针对双足机器人NAO爬楼梯步态规划问题,提出一种离线步态规划方法：基于几何法建立机器人爬楼梯逆运动学模型;将运动解耦为前向运动和侧向运动,对于起步、中步和止步三个阶段,采用加速度空间法和几何约束规划法,计算各关节运动轨迹,并基于其逆运动学模型,得到各关节角序列;分别基于NAOSim和NAO进行虚拟样机仿真实验和实物样机验证.实验结果表明,步态规划方法合理有效.     

NAO机器人干预治疗自闭儿童的人机交互应用平台

本文利用NAO机器人的本体感知硬件,通过软件编程实现NAO在视觉、语音、触觉等多感知通道与人交互,并根据自闭症儿童的性格差异和康复原理,综合运用多通道技术设计了一套干预治疗自闭症儿童的模块。通过实验发现,自闭症儿童在与NAO的交互过程中充满了好奇心,并能积极主动地与NAO互动。结果表明,通过适合的自闭症干预治疗模块可以提高自闭症儿童的社交能力。     

NAO机器人在自闭症干预中的应用

描述了自闭症谱系障碍（ASD）患儿基于人形机器人NAO人机互动情况下和在普通课堂环境下的行为反应,并给出其在干预治疗及普通课堂环境下的评估结果。大量实验结果表明,基于NAO机器人的人机互动干预过程中患儿自闭症状行为较普通课堂大大减少,其症状得到有效控制。因此可得出结论：人形机器人NAO可以作为帮助自闭症谱系障碍患儿干预治疗的平台。     

RoboCup中NAO机器人球场目标红球识别与快速找球策略

根据RoboCup中NAO机器人足球比赛的规则,机器人通过对颜色的识别来识别球场上的物体及环境。文章分析了RGB颜色空间的优缺点,采用HSV作为视觉系统的颜色空间,减弱了现场光照变化对视觉系统产生的影响。文章提出了一种基于HSV色彩空间下识别红球的方法,然后提出一种简单的追踪红球策略,与测距追踪实际效果相比较,发现这种追踪策略更符合实际场景应用。     

未知异构非线性多智能体系统的无模型自适应编队控制

研究一类未知异构非线性多智能体的编队控制问题.首先,利用全格式动态线性化(full form dynamic linearization,FFDL)方法将未知非线性智能体转化为含有时变参数的数据模型,并给出时变参数的估计方法;然后,基于该数据模型设计一种分布式无模型自适应多智能体编队控制方案;最后,为验证所提出的无模型自适应编队控制方案的有效性,利用3台NAO机器人开发基于Python的多智能体编队控制实验平台.实验比较结果表明,通过所提出的控制方案可使3台机器人仅利用局部信息就能有效完成编队控制任务,控制性能优于基于PID的编队控制方法.     

RoboCup标准平台NAO机器人目标识别与自定位研究

RoboCup标准平台比赛（SPL）,由于环境的动态性,需要NAO机器人根据场上情况快速稳定地确定自身位姿状态。介绍了一种基于KD树的最近邻搜索实现特征匹配建立色表、通过颜色识别进行场地建模、根据单目视觉测距来实现NAO机器人的自定位的方法。实验证明,方法在各种复杂的环境影响下,能够快速有效的识别目标,并准确的实现机器人的自定位。     

基于稳态视觉诱发电位的在线脑机接口研究

针对脑机接口中存在的抗噪声能力差、操作复杂的问题,利用便携式脑电采集设备Emotiv EPOC以及NAO机器人,搭建了一个抗噪能力较好的稳态视觉诱发在线脑机接口系统。该系统采用典型相关性分析进行稳态视觉诱发电位的频率识别。在线实验中受试者通过Emotiv控制NAO机器人运动,四类任务的准确率达到87.50%。在线实验没有回避周围的噪声,表明该系统具有较好的抗噪能力。     

NAO机器人现身RoboCup公开赛

10月19日,2013中国机器人大赛暨RoboCup公开赛在安徽建筑大学正式托歼帷幕,本次比赛包括RoboCup仿真组、RoboCiIp标准平俞组、RoboCup家庭机器人组等112个项目、日前的标准平台组以法困AldebaranRobotics公司的NAO机器人作为机器人比赛平台,     

从NAO感知系统看机器人的设计

本文从硬件设计的角度出发,在分析机器人传感系统的基础上,重点分析了典型的机器人——NA0的感知系统,包括音频系统、视觉系统和运动系统.通过基于硬件设计的具体实例分析,对未来机器人设计进行了展望.     

Development of tethered autonomous mobile robot systems for field works

This paper describes the implementation details, advantages and potential applications of autonomous tethered mobile robot systems using the 'hyper-tether' concept. Hyper-tether is a new research area on tethered connections, which provide tethering among different mobile robot types, such as a robot with the environment and a robot with humans and animals. Its basic function is to actively control the tether's tension and/or length, but it also considers tether launching, anchoring, power delivery, data communication cabling and built-in trajectory command generation capabilities. Many of these features can be efficiently applied to build a tethered mobile robot system which remotely manipulates a working tool that can be useful for land-mine detection and removal, trimming of gardens and grass cutting of wide areas (e.g. golf courses, soccer and baseball fields), spraying of agricultural chemicals, forestry and construction works, etc. In this paper, a simple prototype of hypertether's winch-tether pair and a working tool equipped with a grass cutter was constructed, and basic experiments were performed to demonstrate the validity of the proposed system.     

Integration of vision and walking skills together with high-level strategies for quadruped robots to play soccer

Legged robots taking part in real multi-agent activities represent a very innovative challenge. This domain of research requires developments in three main areas. First, without any feedback information from the environment, there is no way for robots to achieve some tasks autonomously. Fortunately, the quadruped 'Sony' prototypes on which all experiments are carried out are equipped with an enhanced vision system; thanks to its CCD camera located in its head, the robot can obtain color images of the scene around it. Extracting relevant information from the images captured is not easy since it must be done onboard in real time. Moreover, image treatment procedures should have high process rates for the robot to react quickly in front of unexpected events. A special vision module composed of three parts has been designed for these purposes. The second point to focus on is the walking ability of the robot. Quadrupeds are designed to move efficiently and rapidly on flat ground. The objective of the walking module is to generate appropriate walking patterns allowing the machine to walk in the desired direction. Walking gaits are produced like reflexes by the robot itself to adapt to the situation. With regard to the design of these gaits, emphasis has been put on increasing speed and mastering transitions. Finally, the machine should be given a minimum of intelligence since it has to manage vision information and its walking gaits by itself. When involved in situations of cooperation or competition or both, like in a soccer game, a high-level supervision task is welcome. This paper presents detailed developments of these three points and describes how they are implemented on a real robot.     

不完全信息博弈的机器人对抗决策

针对机器人比赛时局势的动态变化给机器人对抗决策博弈局面带来的不完全性问题,提出了豪尔绍尼转换和贝叶斯均衡相融合的不完全信息博弈算法,该算法克服了博弈局势中对未知信息的盲目"猜测".以机器人足球比赛时的数据为背景建立不完全信息博弈模型,研究机器人的决策对抗系统.仿真结果表明,不完全信息博弈算法可以使得机器人进行较优策略的选择,从而进一步提高机器人在比赛中的自主性和智能性.     

A Visual-Based Gesture Prediction Framework Applied in Social Robots

In daily life, people use their hands in various ways for most daily activities. There are many applications based on the position, direction, and joints of the hand, including gesture recognition, gesture prediction, robotics and so on. This paper proposes a gesture prediction system that uses hand joint coordinate features collected by the Leap Motion to predict dynamic hand gestures. The model is applied to the NAO robot to verify the effectiveness of the proposed method. First of all, in ord...     

扫地机器人增强位姿融合的Cartographer算法及系统实现

Cartographer是谷歌在2016年开源的一个可以在多传感器配置下实现低计算资源消耗的SLAM算法框架.本文针对原有Cartographer中位姿融合不准确,存在延迟的问题,首先设计了一种基于位姿增量的多传感器位姿融合方法;随后针对扫地机器人Player平台,设计并实现基于增强Cartographer算法的多模块SLAM系统;最后通过Cartographer数据集的实验分析和真实场景的实际测试,本论文验证了增强Cartographer算法的有效性以及SLAM系统在Player机器人平台上的可用性.     

基于ROS的服务机器人云端协同计算框架

随着机器人应用技术的发展,服务机器人走进人们的生活日渐成为可能. 但机器人本身计算能力有限,同时仅靠自身的传感器接收的信息也有一定的局限性. 现有的机器人还不足以胜任面对复杂场景的应对能力,也不能够满足人们对服务机器人的期待. 本文设计的云机器人计算框架（cloud robot computing framework, CRCF）通过云端,将智能家居以及其他智能硬件与机器人相结合,为机器人提供更多更广的信息. 同时,CRCF通过互联网结合了其它第三方的云端应用API,为机器人提供更多的服务功能. CRCF框架旨在利用云端的大数据处理能力提升机器人的计算和存储能力,并结合第三方云端应用服务和智能硬件设备来拓展机器人的信息来源和服务功能. 最后,本文通过远程语音控制机器人的实验,验证了CRCF系统平台在结合硬件设备以及第三方云端应用的功能和性能.     

基于高斯牛顿法的可匹配机器人高精度自动抓放料方法

为了提高可匹配机器人抓料和放料精度,降低抓放料过程中的次品率,提出了基于高斯牛顿法的可匹配机器人高精度自动抓放料方法;通过可匹配机器人抓放料工作站,放置工件原料和成品,针对可匹配机器人夹取能力,设计机器人夹具结构,优化爪臂和驱动装置,增加防滑胶套,设计可匹配机器人自动抓料和放料装置;建立可匹配机器人移动坐标系,构建可匹配机器人自动抓放料数学模型,采用高斯牛顿法,根据泰勒级数展开式,迭代求解可匹配机器人自动抓放料数学模型;利用动态机械工具位姿,调整机器人自定义世界坐标系位姿,校正可匹配机器人自动抓放料误差,实现可匹配机器人高精度自动抓放料;实验结果表明,所提方法的平均抓料和放料准确率分别为92％和95％,抓料和放料过程中次品率分别为0.89％和0.64％,能够有效提高抓料和放料精度,降低抓料和放料过程中次品率.     

Adaptive Social Robot for Sustaining Social Engagement during Long-Term Children–Robot Interaction

One of the known challenges in Children–Robot Interaction (cHRI) is to sustain children’s engagement during long-term interactions with robots. Researchers have hypothesized that robots that can adapt to children’s affective states and can also learn from the environment can result in sustaining engagement during cHRI. Recently, researchers have conducted a range of studies where robots portray different social capabilities and have shown that it has positively influenced children’s engagement. However, despite an immense body of research on implementation of different adaptive social robots, a pivotal question remains unanswered: Which adaptations portrayed by a robot can result in maintaining long-term social engagement during cHRI? In other words, what are the appropriate and effective adaptations portrayed by a robot that will sustain social engagement for an extended number of interactions? In this article, we report on a study conducted with three groups of children who played a snakes and ladders game with the NAO robot to address the aforementioned question. The NAO performed 1) game-based adaptations, 2) emotion-based adaptations, and 3) memory-based adaptation. Our results showed that emotion-based adaptations were found out to be most effective, followed by memory-based adaptations. Game adaptation didn’t result in sustaining long-term social engagement.     

一种适用于踏步机的游戏设计

为了使大众能方便地在室内进行健身,根据市场上已有的踏步器为蓝本,设计一款适用于踏步器的游戏系统,它溶健身娱乐为一体,适合现代人的生活方式.该系统由三部分组成：踏步器、传感装置和计算机.传感装置由两个霍尔传感器、MAX232串口芯片和STC89C52单片机组成,霍尔传感器用来感应玩家踏板动作,单片机用于计算左、右步频并发送步频,串口芯片将左、右步频数据传给计算机;计算机负责游戏软件的运行和显示.游戏软件的设计原理是：左、右步频的平均值可用来决定游戏主角的移动速度,步频差决定它的移动方向.改编了“贪吃蛇”游戏作为测试软件,在游戏中添加了运动控制和健身功能,经过测试能达到预期的设计效果.该游戏系统具有制作成本低、操控方便、通用性强等特点,具备一定的市场开发潜力.     

Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot

The ability of autonomous navigation of the humanoid robot under unknown environment is very important to real-life applications. EKF-SLAM based on the camera recognition and laser detection for humanoid robot NAO is presented in this paper. Camera recognition is used to recognize if the object is a landmark. Because the computational resources needed for the feature-based position estimation are quite expensive, the laser instead of the camera provides the position of the landmark. A fractional order proportional-integral (PI) controller is designed to reduce the derivation of the NAO robot from the desired path during autonomous navigation. Experiments show that the proposed method is valid and reliable for autonomous navigation of the NAO robot under unknown environment.