基于嵌入式系统的服务机器人研究与开发

本文设计并实现了一种服务机器人系统,采用嵌入式系统,传感器阵列,语音识别与语音合成技术、无线数据通信技术,能够完成人脸跟踪、语音交互、自主移动、动作响应、远程遥控.实际实验表明,该机器人能够和人进行自然的交互,可以为人类提供一定的机器人服务功能.     

基于智能手机控制的家居服务机器人研发

针对我国智能家居服务机器人的发展现状与不足,设计了一种基于智能手机控制的家居服务机器人。主要涉及技术有:机器导航、机器视觉、信息融合、人机交互、嵌入式技术、语音识别技术等。实现了实时定位、远程控制、自主导航、手势识别、监控家庭环境、语音识别等功能。机器人配有一个单目摄像头,可以实时监控家庭环境;通过智能手机远程控制端可以在世界上任何一个可以上网的地方看到用户家里的状况;并且可以用手机控制机器人的行走路径,真正做到全方位无盲点的实时监控;基于ARM平台的嵌入式视觉处理系统实现手势识别并准确的控制机器人运动;机器人还配有烟雾感传感器、温湿度传感器,可以监测环境的空气质量。经过试验验证,该机器人符合家居服务的基本要求。     

基于人工心理的机器人平台的研究与实现

本文提出并实现了一种基于人工心理的机器人平台。平台采用上下位机结构,上位机采用嵌入式PC,利用语音合成与识别技术、图像识别与处理技术实现多通道人机交互,利用人工智能和人工心理理论建立数学模型,实现机器人的智能化和情感化交互;下位机采用PIC单片机系统实现机器人的行为控制。实验结果表明,机器人可以与人实现和谐的情感智能交互。     

多舵机控制在可遥操作个人机器人上的应用

文章介绍的机器人的实现了GSM短信息远程控制技术和基于GPS的自主定位技术。机器人能够模仿人类的动作行为是机器人学的一个研究重点,本文提出了一种多舵机控制方法,实现了机器人学习并模仿人类的动作。通过语音识别和语音合成技术实现机器人和人自然和谐交互。     

基于意图识别的智能语音交互机器人设计

为提高智能语音交互机器人语音交互的准确率,提出一种基于意图识别的机器人智能英语语音交互方法。通过引入Glove＿BiGRU＿Self-attention分类预测模型构建意图识别功能模块,并采用ROS分布式架构对系统功能模块进行整合,实现人机的智能语音交互。仿真结果表明,采用所提方法进行的语音意图识别,具有更高的准确率,相较于基于DCNN模型、基于CNN-LSTM模型与基于单向构建的GRU-Self-attention模型的意图识别方法,识别准确率分别高出8.03%、4.07%和2.14%,具有更好的识别效果;在特征提取上,训练时间较传统基于BiLSTM模型的提取方法,BiGRU的训练时间缩短了4倍,训练效率更高。实验结果表明,采用所提意图识别方法搭建的语音交互系统,对用户英语语音指令的识别准确率和识别效率依然拥有较好的结果,识别平均准确率达到了89.72%,识别时间均在0.35 s之内,证明所提方法可以应用于实际语音交互之中。应用实验表明,采用基于意图识别方法搭建的智能语音交互机器人,无论是在问答交互还是控制命令上,都可以准确对用户英语指令进行识别,根据用户要求进行相关回答或完成相应动...     

语音交互导览机器人的设计

为提高公共场馆的讲解服务效率和趣味性,设计了一款语音交互导览机器人.该机器人采用科大讯飞AIUI新一代软硬件语音交互解决方案提升人机交互的智能化水平,机器人基于AGV磁导航和RFID射频识别技术实现自主定位导航,应用多种无线通信技术,解决机器人与场馆设备的通信控制问题,实现讲解过程中机器人与场馆设备的联动,使用STM32系列微控制器进行数据处理与系统控制,采用C语言编写机器人底层代码,系统采用标准ModBus通信协议,提高系统通信可靠性.论文设计的语音交互导览机器人具有操作简单、智能化水平高、运行可靠等特点.     

服务机器人语音交互解决方案

在分析人类的认知过程、人类智能本质以及在脑小脑分工和协调配合工作机理的基础上,研究了远程大脑和机器人本体上小脑的分工、系统结构、工作原理,并构建了具有仿生功能的远程脑机器人控制体系。讨论了基于远程脑概念的服务机器人开发平台中语音交互的地位和作用;介绍了基于组件技术的大脑相关的语音交互系统设计,以及基于嵌入式系统的机器人本体相关的语音功能实现。实际应用表明,该套综合解决方案具有较好的灵活性、智能性和实用性。     

基于云平台的智能语音交互机器人设计

现有的语音交互机器人多采用用户提问、机器人回答的单向交流方式,人机交互的智能性和灵活性较差。本文研究运用树莓派(Raspberry Pi)计算机和配套的语音板作为硬件载体,融合语音唤醒、语音识别、语音合成、自然语言处理等人工智能技术,调用科大讯飞开放云平台、在线图灵机器人,搭建一种基于云平台的智能语音交互机器人系统,并结合自主开发的本地知识库和问题库,使智能语音交互机器人能够根据不同环境与任务需求实现双向互动交流,实现由机器人采集信息和交流反馈,以提供高适应性的无接触人机语音交互服务。     

嵌入式Arduino系统物联网机器人的研发与应用

在21世纪飞速发展的社会中,人们越来越向往智能生活,物联网机器人能最大限度实现智能生活。笔者设计并实现了一种嵌入式系统的物联网服器人,该机器人系统主体由四麦克纳姆轮、Arduino控制器、Arduino扩展板、传感器列阵、WLAN无线通信以及语音检测、图像智能识别等模块构成,并将该系统与现代智能家居有效结合,构成一种新型物联网平台。Arduino机器人在检测到复杂情况时可以精准发出远程警报,能较有效地异地操控家中的智能家居,出色地完成语音识别和人机对话,并通过视觉追踪实现自动跟拍等功能。该服务机器人为进一步实现智能、安全物联网提供一种新的可能,拥有广阔的应用和发展前景。     

语音信息的身份和指令识别方法应用

针对智能机器人系统对语音交互功能的实际需求, 在DM-B200开放式机器人平台上,设计并实现了基于语音信息的说话人身份识别功能和语音指令识别功能. 为了准确识别特定说话人的身份, 采用了矢量量化的识别方法, 而为了提高机器人语音控制的实时性, 语音指令识别采用了动态时间规整的方法. 应用结果表明, 所设计的语音识别系统达到96%以上的综合识别率, 具有实际应用价值.     

End-user programming architecture facilitates the uptake of robots in social therapies

This paper proposes an architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to different situations. It aims to facilitate the uptake and actual use of robot technologies in therapies for training social skills to autistic children. However, the framework is easy to generalize for an arbitrary human–robot interaction application, where users with no technical background need to program robots, i.e. in various assistive robotics applications. We identified the main needs of end-user programming of robots as a basic prerequisite for the uptake of robots in assistive applications. These are reusability, modularity, affordances for natural interaction and the ease of use. After reviewing the shortcomings of the existing architectures, we developed an initial architecture according to these principles and embedded it in a robot platform. Further, we used a co-creation process to develop and concretize the architecture to facilitate solutions and create affordances for robot specialists and therapists. Several pilot tests showed that different user groups, including therapists with general computer skills and adolescents with autism could make simple training or general behavioral scenarios within 1 h, by connecting existing behavioral blocks and by typing textual robot commands for fine-tuning the behaviors. In addition, this paper explains the basic concepts behind the TiViPE based robot control platform, and gives guidelines for choosing the robot programming tool and designing end-user platforms for robots.     

Bridging the reality gap between the Webots simulator and e-puck robots

This work presents a set of techniques to improve the cross-compatibility between the Webots simulator and the educational e-puck mobile robot. The work is motivated by the need of a realistic simulation environment, especially designed to consider the unique challenges associated to multi-robot systems (MRS), such as the robot–robot interaction (RRI). This article starts by proposing a new Webots programming architecture that provides full control of the e-puck’s firmware. By doing so, one can easily improve the already existing e-puck’s functionalities on Webots, as well as adding new functionalities required by most MRS applications. Among the range of new possible functionalities, this article describes the successful implementation of the microphone, the speaker, and the Bluetooth for robot–robot communication. Due to the limitations of the e-puck’s Bluetooth modules, this work goes even further by bringing some insights about the Gumstix Overo COM turret and how robot–robot communication may be achieved using WiFi technology. The outcomes provided by the experiments conducted using both virtual and real e-pucks under the Webots framework open new doors for low-cost multi-robot applications.     

基于人机交互的机械臂位姿自动监视系统设计

为了提高机械臂位姿自动监视和控制能力,提出一种基于人机交互的机械臂位姿自动监视系统设计方法,系统设计包括机械臂的位姿自动控制算法设计和系统硬件设计两部分,采用粒子滤波位姿跟踪方法进行机械臂的动态定位位姿参数信息采集和融合处理,在动态和静态环境下,结合加速全局定位方法进行机械臂位姿自动监视的人机交互设计,构建机械臂人机交互的动态定位控制模型,采用自适应位姿跟踪方法实现对机械臂的位姿自动监视,通过捕捉未知目标的质量特性参数,实现机械臂的位姿自动监视和人机交互设计。通过DSP和嵌入式ARM实现对机械臂位姿自动监视系统的硬件设计。测试结果表明,采用该方法进行机械臂位姿自动监视的自动化水平较高,智能性较好,提高了机械臂的位姿自动监视和控制能力。     

Online learning design of an image-based facial expression recognition system

In order to serve people and support them in daily life, a domestic or service robot needs to accommodate itself to various individuals. Emotional and intelligent human–robot interaction plays an important role for a robot to gain attention of its users. Facial expression recognition is a key factor in interactive robotic applications. In this paper, an image-based facial expression recognition system that adapts online to a new face is proposed. The main idea of the proposed learning algorithm is to adjust parameters of the support vector machine (SVM) hyperplane for learning facial expressions of a new face. After mapping the input space to Gaussian-kernel space, support vector pursuit learning (SVPL) is employed to retrain the hyperplane in the new feature space. To expedite the retraining step, we propose to retrain a new SVM classifier by using only samples classified incorrectly in previous iteration in combination with critical historical sets. After adjusting the hyperplane parameters, the new classifier will recognize more effectively previous unrecognizable facial datasets. Experiments of using an embedded imaging system show that the proposed system recognizes new facial datasets with a recognition rate of 92.7%. Furthermore, it also maintains a satisfactory recognition rate of 82.6% of old facial samples.     

Designing an API at an appropriate abstraction level for programming social robot applications

Whilst robots are increasingly being deployed as social agents, it is still difficult to program them to interact socially. To create usable tools for programming these robots, tool developers need to know what abstraction levels are appropriate for programming social robot applications. We explore this through the iterative design and evaluation of an API for programming social robots. The results show that high level primitives, with a close mapping to social interaction, are suitable for programming social robot applications. However, the abstraction level should not be so high that it takes away too much control from programmers. This has the potential to enable programmers to produce high quality social robot applications with less programming effort.     

一种基于SSVEP的仿人机器人异步脑机接口控制系统

设计了稳态视觉诱发电位(SSVEP)空闲状态检测的特征提取方法,建立了基于SSVEP的异步脑机接口二级分类器结构,开发了基于TICC2430芯片的无线传感器网络模块,实现了机器人控制命令的远程传送,使该仿人机器人系统具有脑电控制、语音交互、游戏手柄交互、机器视觉与避障等功能.通过SSVEP窄闲状态检测实验验证了脑机接口...     

康复辅助机器人及其物理人机交互方法

面对中国社会快速老龄化现状和庞大的残疾人群,康复辅助机器人研究具有重要学术价值和广阔的应用前景.康复辅助机器人研究涉及神经科学、生物力学、机器人自动控制等领域知识,是机器人最具挑战性和最受关注的研究领域之一.与其他机器人不同,康复辅助机器人的作用对象是人,存在人与机器人的信息交流和能量交换,物理人机交互控制方法是其研究核心和关键技术.本文以神经康复机器人、穿戴式外骨骼、智能假肢等应用为例,介绍当前的研究现状,并重点介绍人体运动意图识别方法和交互控制方法等研究重点和难点.最后展望该领域的未来技术发展方向.     

Accelerating embedded image processing for real time: a case study

Many image processing applications need real-time performance, while having restrictions of size, weight and power consumption. Common solutions, including hardware/software co-designs, are based on Field Programmable Gate Arrays (FPGAs). Their main drawback is long development time. In this work, a co-design methodology for processor-centric embedded systems with hardware acceleration using FPGAs is proposed. The goal of this methodology is to achieve real-time embedded solutions, using hardware acceleration, but achieving development time similar to that of software projects. Well established methodologies, techniques and languages from the software domain—such as Object-Oriented Paradigm design, Unified Modelling Language, and multithreading programming—are applied; and semiautomatic C-to-HDL translation tools and methods are used and compared. The methodology is applied to achieve an embedded implementation of a global vision algorithm for the localization of multiple robots in an e-learning robotic laboratory. The algorithm is specifically developed to work reliably 24/7 and to detect the robot’s positions and headings even in the presence of partial occlusions and varying lighting conditions expectable in a normal classroom. The co-designed implementation of this algorithm processes 1,600 × 1,200 pixel images at a rate of 32 fps with an estimated energy consumption of 17 mJ per frame. It achieves a 16× acceleration and 92 % energy saving, which compares favorably with the most optimized embedded software solutions. This case study shows the usefulness of the proposed methodology for embedded real-time image processing applications.     

基于嵌入式系统的中文输入法的设计与实现

中文输入是中文应用软件进行人机交互必不可少的部分，目前在嵌入式系统中广泛使用的图形系统都不支持中文输入。该文提出了一种在嵌入式图形系统中实现中文输入的方案，介绍了目前几种流行的嵌入式图形系统，阐述了中文输入法实现的基本原理和算法，给出了该中文输入法在不同嵌入式图形系统中的实现方法和示例。