红外传感器在教育机器人避障电路设计中的应用

红外传感器在家用电器遥控和机器人避障方面有着广泛的应用,笔者根据红外传感器的这一特性设计出一款教育机器人避障电路,介绍了红外传感器在机器人避障电路中的应用,给出红外传感器与单片机系统的硬件接口电路和避障软件的编程思路,并通过测试,得出了影响红外传感器避障的相关因素,并提出了改进的方法和措施.     

传感器在多关节机器人系统实时避障中的应用

评述近几年来在多关节机器人系统实时避障中传感器技术的应用,详细介绍了传感器的选择及多传感器信息融合技术,并指出这一领域中值得进一步研究的一些问题和可能的发展方向．     

多传感器信息融合在机器人避障中的应用

本文在移动机器人的避障系统中,充分利用数字信号处理器(DSP)超强的运算能力,以及单片机(MCU)善于控制的特点,构造了DSP+MCU的双CPU系统,并且利用粗糙集理论进行多传感器信息融合,实现了移动智能机器人在不确定环境中实时获取外部信息,快速地实现避障.     

基于多信息融合的智能车避障系统的设计与实现

随着无人驾驶技术的快速发展,智能车在复杂环境中的避障成为制约其实际应用的关键问题。针对单一传感器避障方案在实时性和可靠性方面的不足,本文提出了一种基于多信息融合的智能车避障系统。硬件采用单片机实现多传感器信息并行处理,集成多个模块;软件通过卡尔曼滤波算法融合摄像头、TOF采集的多源数据定位障碍物,结合陀螺仪数据、增量式PID、Bug2和人工势场算法进行巡线和避障,构建了感知-决策-执行一体化的智能车避障系统。     

基于声纳环传感器的机器人避障研究

任何一种移动机器人要实现未知环境自主导航都必须有效而可靠地感知环境信息,而超声波传感器在检测障碍物距离信息方面应用十分广泛。介绍了旅行家II号声纳环传感系统的设计与实现原理,并对声纳的精度进行了测试。在此基础上,提出了移动机器人一种简单避障策略,并运用2种基本避障实验:静态避障和动态避障,验证了该避障策略的正确性和有效性。     

热释电红外传感器在防盗系统中的应用

介绍一种自动防盗报警系统。该系统由热释电红外传感器、电话和检控电路组成。若有人体在警戒范围内移动 ,红外传感器检测出信号 ,检控电路使电话自动拨号 (如 110 ) ,并通过其中的语言电路报告现场地址。     

基于单片机的智能车避障的实现

主要介绍了一种具有避障功能的智能小车的设计方案。该方案以AT89S52为整个系统的核心,使用不同频率的两种红外对管进行避障,用红外LED发射管在障碍区外形成一个隐形的安全区,850nm红外和940nm的红外发射二极管均匀分布在障碍区圆上,通过单片机处理红外对管传输过来的数据从而实现智能控制,达到避障的目的。     

基于多超声波传感器避障机器人小车的设计

本文介绍了采用多超声波传感器的避障小车的设计与实现.通过多个超声波发送脉冲检测与障碍物间的距离,控制方向舵机进行转向,实现小车的避障功能.小车采用前轮舵机转向,后轮H桥驱动电路和齿轮减速驱动的方式,以Arduino Mega ADK控制板作为控制核心,进行了软硬件系统的设计,搭建出自动避障小车平台,取得了良好的实验效果.     

基于AVR单片机的智能车避障系统的实现

本设计方案以ATmega128为系统的核心,借助超声波传感器,提出一种超声波三角形测距定位的方法,结合模糊控制理论和PI控制算法,设计出一种模糊-PI双模控制器,用于控制智能车,实现了智能车户外智能避障,高速稳定运行。     

Abstracting Vehicle Shape and Kinematic Constraints from Obstacle Avoidance Methods

Most obstacle avoidance techniques do not take into account vehicle shape and kinematic constraints. They assume a punctual and omnidirectional vehicle and thus they are doomed to rely on approximations when used on real vehicles. Our main contribution is a framework to consider shape and kinematics together in an exact manner in the obstacle avoidance process, by abstracting these constraints from the avoidance method usage. Our approach can be applied to many non-holonomic vehicles with arbitrary shape. For these vehicles, the configuration space is three-dimensional, while the control space is two-dimensional. The main idea is to construct (centred on the robot at any time) the two-dimensional manifold of the configuration space that is defined by elementary circular paths. This manifold contains all the configurations that can be attained at each step of the obstacle avoidance and is thus general for all methods. Another important contribution of the paper is the exact calculus of the obstacle representation in this manifold for any robot shape (i.e. the configuration regions in collision). Finally, we propose a change of coordinates of this manifold so that the elementary paths become straight lines. Therefore, the three-dimensional obstacle avoidance problem with kinematic constraints is transformed into the simple obstacle avoidance problem for a point moving in a two-dimensional space without any kinematic restriction (the usual approximation in obstacle avoidance). Thus, existing avoidance techniques become applicable. The relevance of this proposal is to improve the domain of applicability of a wide range of obstacle avoidance methods. We validated the technique by integrating two avoidance methods in our framework and performing tests in the real robot. Javier Minguez received the physics science degree in 1996 from the Universidad Complutense de Madrid, Madrid, Spain, and the Ph.D. degree in computer science and systems engineering in 2002 from the University of Zaragoza, Zaragoza, Spain. During his student period, in 1999 he was a research visitor in the Robotics and Artificial Intelligence Group, LAASCNRS, Toulouse, France. In 2000, he visited the Robot and ComputerVision Laboratory (ISR-IST), Technical University of Lisbon, Lisbon, Portugal. In 2001, he was with the Robotics Laboratory, Stanford University, Stanford, USA. He is currently a fulltime Researcher in the Robot, Vision, and Real Time Group, in the University of Zaragoza. His research interests are obstacle avoidance, motion estimation and sensor-based motion systems for mobile robots. Luis Montano was born on September 6, 1958 in Huesca, Spain. He received the industrial engineering degree in 1981 and the PhD degree in 1987 from the University of Zaragoza, Spain. He is an Associate Professor of Systems Engineering and Automatic Control at the University of Zaragoza (Spain). He has been Head of the Computer Science and Systems Engineering Department of the University of Zaragoza. Currently he is the coordinator of the Production Technologies Research in the Aragon Institute of Engineering Research and of the Robotics, Perception and Real Time group of the University of Zaragoza. He is principal researcher in robotic projects and his major research interests are mobile robot navigation and cooperative robots. José Santos-Victor received the PhD degree in Electrical and Computer Engineering in 1995 from Instituto Superior Técnico (IST - Lisbon, Portugal), in the area of Computer Vision and Robotics. He is an Associate Professor at the Department of Electrical and Computer Engineering of IST and a researcher of the Institute of Systems and Robotics (ISR), at the Computer and Robot Vision Lab - VisLab. (http://vislab.isr.ist.utl.pt) He is the scientific responsible for the participation of IST in various European and National research projects in the areas of Computer Vision and Robotics. His research interests are in the areas of Computer and Robot Vision, particularly in the relationship between visual perception and the control of action, biologically inspired vision and robotics, cognitive vision and visual controlled (land, air and underwater) mobile robots. Prof. Santos-Victor is an IEEE member and an Associated Editor of the IEEE Transactions on Robotics.     

一种语音控制的自主循迹与避障的智能小车的设计

智能小车以SPCE061A单片机为控制核心,采用反射性光电探测器对白纸上的黑色路径进行探测,按照预定的路径行驶。借助SPCE061A的语音特色,采用语音控制和中断定时控制相结合的方法,实现了通过语音对小车进行控制。实验结果表明,小车工作稳定,能够自主循迹与避障。     

一种语音控制的自主寻迹与避障智能小车设计

智能小车以STC12C5A60S2单片机为控制核心,采用反射型光电探测器RPR-220对白纸中的黑色路径进行探测,按照预定的路径行驶,小车运用短距离无线通信模块NRF24L01将行驶状况传输给计算机;计算机运行VB软件设计的人机交互接口软件显示小车行驶状况,它还可通过微软的Speech SDK5.3识别操作者发出的语音指令,对小车进行控制。实验结果表明小车工作稳定,能够自主寻迹与避障,操作者可以遥控小车的行驶速度与方向。     

基于模糊控制的超声波避障方法的研究

依据移动机器人上超声波传感器的布置和分组情况,将反映移动机器人当前感知环境的期望类别进行了概括。在此基础上分析了移动机器人的模糊避障原理,并建立了一种基于人的驾驶经验的模糊逻辑控制的路障躲避方法。通过对人的驾驶经验的分析,针对移动机器人建立了路障躲避的模糊规则,并给出了输入与输出变量的隶属度函数。在Simulink中模拟机器人行驶的环境,建立相应的模型对系统进行仿真,结果表明移动机器人能实现自主行驶。     

起重吊装多机器人系统协作避障规划研究

针对起重吊装多机器人系统实际作业情况,进行了该机器人系统协作避障规划研究.首先,基于栅格法提出了优化姿态转角--动态栅格法的路径规划改进算法;其次,设计了基于传感器技术的自适应协作系统.该协作避障方法具备了寻找全局最优路线的能力,同时实现了多机器人系统内部的稳定协调合作;最后,建立了Matlab与LabVIEW联合仿真系统,仿真结果表明该系统是可行且高效的.     

基于多特征融合的防爆自动导引车避障方法研究

为解决在工厂环境中防爆自动导引车(Automated Guided Vehicle,AGV)难以在不同光照条件下实现行人检测的问题,本文提出将"结构光+双目视觉相机"的图像采集方案应用于爆炸性危险环境.针对传统的基于RGB(代表红、绿、蓝三个通道的颜色)图像的HOG-LBP(Histogram of Oriented ...     

基于复形法求解多智能体避障问题的研究

该文基于最优化方法中的复形法,对多智能体领域里的机器人足球避障问题,给出了最短路径的解决方法。它在机器人足球避障问题的解法中有其突出的特点。首先,在执行避障动作时,以尽可能小的动作幅度完成了动作执行,此方法应用于多球员的比赛,如11对11,较其它方法尤具优势。其次,以往有关避障问题的解法,计算量大,对机器人奔跑速度影响较大,该文采用复形法求解的数学模型公式,克服了此类缺点,方法简单,计算速度快。在仿真实验里,取得了理想的效果。     

基于超声波传感器的脑控轮椅避障系统的研究

针对脑控轮椅行驶时因用户脑电信号的不稳定性可能引起碰撞事故发生的现象,提出了一种避障方法,并设计了多路超声波传感器避障系统及避障提示反馈界面;反馈界面上实时显示的提示信息将辅助用户做出有效的避障决策;当用户采用脑电自主控制轮椅运行时,若无法成功避障,则该避障系统立即启动紧急停车功能以避免与障碍物发生碰撞,保证了脑控轮椅用户的人身安全;实验结果表明:当把安全区域临界值、前后及左右紧急停车距离临界值分别设置为500mm、400mm和200mm时,该超声波传感器避障系统稳定性好、实时性强,能够满足脑控轮椅的用户安全导航的需要.     

未知环境下的移动机器人定位及实时避障

针对未知环境下移动机器人实时动态避障及定位问题，考虑里程计定位的无界累加误差和动态障碍物环境下实时障碍躲避需要，提出了一种可行的避障定位的策略。该策略融合了机器人内部传感器、里程计、电子罗盘和激光测距仪的同步和异步信息，合理地解决了常规定位过程中的方向迷失问题，对于静态和动态障碍物都能很好地实时躲避，具有很强的抗干扰性和较高的定位精度。实验证明了该方法的有效性和实用性.