移动机器人超声波测距避障系统设计

测距避障是移动机器人适应未知复杂环境的能力之一,准确测出移动机器人和障碍物之间的距离是关键。以dsPIC33FJ256MC710单片机为核心研究设计了一种移动机器人超声波测距避障系统。该系统利用脉冲回波法测距,针对超声波在空气中的传播速度受环境温度的影响,设计了超声波速度温度补偿电路。实验结果表明该超声波测距避障系统测量数据准确,能够满足移动机器人在复杂环境中避障的需求。     

激光雷达测距的机器人最优移动路径选择机制

针对当前机器人最优移动路径选择机制存在误差,工作效率低的缺陷,设计了基于激光雷达测距的机器人最优移动路径选择机制.首先利用人工势场方构建机器人的移动模型,并采用激光雷达测距技术建立栅格地图,然后将障碍物和机器人间的数据引入到坐标系中,经坐标转换映射到栅格地图中,建立障碍物与栅格地图之间联系;最后采用代价函数对机器人移动...     

Teleoperation of a Mobile Robot Using a Force-Reflection Joystick With Sensing Mechanism of Rotating Magnetic Field

Operators’ intelligent and skillful decisions are necessary for the teleoperation of a mobile robot when there are many scattered obstacles. Among the sensors used for environment recognition, the camera is the most popular and powerful. However, there are several limitations in the camera-based teleoperation of a mobile robot. For example, shadowed and curved areas cannot be viewed using a narrow view-angle camera, especially in an environment with bad illumination and several obstacles. Therefore, it is necessary to have other sensory information for reliable teleoperations. In this study, 16 ultrasonic sensors are attached around a mobile robot in a ring pattern to measure the distances to the obstacles and a collision vector is introduced as a new tool for obstacle avoidance, which is defined as the normal vector from an obstacle to the mobile robot. Based on this collision vector, a virtual reflection force is generated to avoid the obstacles and then the reflection force is transferred to the operator who is holding the joystick used to control the mobile robot. Based on this reflection force, the operator can control the mobile robot more smoothly and safely. For this bidirectional teleoperation, a master joystick system using a two-axis hall sensor was designed to eliminate the nonlinear region, which exists in a general joystick with two motors and potentiometers. The effectiveness of the collision vector and force-reflection joystick is verified by comparing two vision-based teleoperation experiments, with and without force reflection.      

基于Kinect深度技术的障碍物在线快速检测算法

针对在未知环境中移动机器人自主导航面临的障碍物实时检测问题,提出了一种基于Kinect深度技术的障碍物在线快速检测算法。在深度摄像机标定基础上,分析了摄像机运动造成视频流中的场景变化,重点研究了室内动态背景下的Kinect深度图像特征和障碍物在线快速检测。建立室内动态背景模型,采用背景减除法和连通体分析提取障碍物并归类,实现了对Kinect视频序列图像的在线快速检测。以轮式移动机器人为实验平台,验证了所提出算法的实时性、准确性和鲁棒性。     

基于ATmega128单片机的机器人路径规划控制器的硬件设计

以ATmage128单片机为核心,提出了一种基于模糊控制的移动机器人路径控制的设计思路,搭建了一个基于人机监督指导的移动机器人智能避障系统。系统预先设定目标,移动机器人通过超声波测物避障,自主移动到达目标。给出了控制系统硬件设计方案,并对系统的显示电路、超声波测距电路、电机驱动电路、无线通信电路等硬件模块接口电路作出了简要描述。该系统各功能模块化,电路简单,易于调试,便于其他功能的扩展,具有较好的工程实用价值。     

武装机动平台测距避障系统设计

为了实现武装机动平台的精准测距和避障,设计本测距系统,采用4组超声波传感器检测武装机动平台周围环境的障碍物信息,以STC12C5412AD单片机为主控芯片,完成武装机动平台测距数据的采集处理,介绍了测距系统的软、硬件设计。该系统设计简单、成本低、实时性好。实验结果表明,该系统具有良好的测距性能,能应用到武装机动平台避障系统中。     

An obstacle detector system based on laser technology

This article describes the implementation of an obstacle detector system based on laser technology (laser pointer) and the associated electronics used for correct and adequate operation. This system is part of a mobile robot that is able to move itself autonomously around an environment where light-colored obstacles are located. The obstacle detector is mainly composed of two functional blocks: a transmitter and a receptor. The idea consists of receiving the reflected power of an emitted laser beam from an obstacle. Using this method, the associated electronics (receptor) are able to estimate the distance from the mobile robot to the obstacle, depending on the received power. The main goal of this work is the implementation and characterization of an obstacle detector system using laser technology to be embedded in an autonomous mobile robot     

轮式移动教育机器人避障方法的研究

对一种轮式移动教育机器人进行了研究,在实验中采用传统的红外传感器使机器人具有避障功能,另外使用新颖的机械式胡须对机器人进行避障设计,达到了预期的避障效果。以胡须避障为例,讨论并解决了避障过程中的卡死问题,并给出了利用BASIC语言编写控制程序的方法。     

基于机器人的多路超声波测距系统设计研究

介绍了机器人采集环境信息的必要性以及超声波传感器在该方面存在的优势，具体说明了8路超声波测丑巨模块的软、硬件的设计方法，并利用大量的实验测试数据，通过最小二乘法对超声波传感器进行了拟合，建立了超声波传感器的测距方程，为超声波传感器的使用提供了较好的数学模型。提出了一种新的多路超声波传感器测距排列方式，同时给出了在AEF—Ⅱ型移动机器人中的实际应用。     

基于双目视觉的移动机器人避障研究

为了实现Pioneer3-AT轮式移动机器人避障的目的,设计了一种移动机器人避障的系统方案。该方案采用一种快速融合图像分割和立体视觉的障碍物定位方法,即利用经典图像处理把障碍物从背景中分割出来,同时提取其轮廓信息进行立体匹配,之后结合摄像头标定结果,实现空间点的三维重建。采用双目视觉和声纳传感器相配合来获得周围障碍物的信息,最终根据模糊控制原理设计了避障规则和避障控制器。通过实际的躲避障碍物实验,实现了移动机器人成功躲避障碍物的功能。实验结果证实了该系统的可行性和有效性。     

一种基于模糊逻辑的滚动窗口路径规划方法

在原有滚动窗口路径规划方法基础上,结合移动机器人与障碍物之间的距离、动态障碍物运动速度、移动机器人与障碍物和目标点的位置关系,提出基于模糊逻辑的滚动窗口路径规划方法。通过对算法的仿真,证明该算法的有效性。     

多传感器信息融合技术在移动机器人障碍探测中的应用

在移动机器人障碍探测中,需要实时准确的感知环境信息,而单一传感器仅能提供部分环境信息,对环境进行描述时存在局限性。提出采用红外传感器和超声波传感器相结合来感知环境信息,完成障碍物信息的采集,并利用自适应加权融合算法实现数据融合的方案。实验仿真结果表明,多传感器数据融合后比单一传感器所采集的数据更接近于真实值,波动性小,并不易受外界环境的影响。该方案较好地满足了移动机器人障碍探测的需要,具有一定的有效性和实用性。     

基于模糊算法的移动机器人路径规划

为了解决移动机器人最优路径规划问题,提出一种基于模糊算法的移动机器人路径规划策略.利用超声波传感器对环境进行探测,得到关于障碍物和目标的信息.运用模糊推理将障碍位置信息与目标位置信息模糊化,建立模糊规则并解模糊最终使机器人可以很好的避障,从而实现了移动机器人的路径规划.仿真实验结果表明了模糊算法优于势场法和A*算法,具...     

一种针对大型凹型障碍物的组合导航算法

针对移动机器人导航过程中无法规避大型凹型障碍物问题,该文提出一种多状态的组合导航算法。算法按照不同的运动环境,将移动机器人的运行状态分类为运行态、切换态、避障态,同时定义了基于移动机器人运行速度和运行时间的状态双切换条件。当移动机器人处于运行态时,采用人工势场法(APFM)进行导航,并实时观测毗邻障碍物的几何构型。在遭遇障碍物时,切换态用于判断是否满足状态切换条件,以进入避障态执行避障算法。避障完成后,状态自动切换回运行态继续执行导航任务。多状态的提出,可有效解决传统人工势场法在大型凹形障碍物的避障过程中存在局部震荡的问题。基于运行速度和运行时间的双切换条件判定算法,可实现多状态间的平滑切换。实验结果表明,该算法在解决局部震荡问题的同时,还可降低避障时间,提升导航算法效率。     

A behavior-based mobile robot with a visual landmark-recognition system

In this paper, based on behavior-based artificial intelligence we have built a fully autonomous mobile robot. Several modules are developed for the mobile robot to implement different levels of competences and behaviors, where each module itself generates behaviors. New modules can be easily added to the robot system to improve in the competence without changing any existing modules. A vision-based landmark recognition system for robot navigation is developed as the highest layer in the subsumption architecture. A genetic-algorithm-based search method for pattern recognition of digital images is proposed and implemented to recognize artificial landmarks by searching all the predefined patterns. The vision layer is capable of generating the desired behaviors corresponding to various landmarks. A combination of eight ultrasonic sensors is designed to implement obstacle-avoidance behaviors through a set of fuzzy rules. The effectiveness of this behavior-based mobile robot is demonstrated by experimental studies.     

基于超声波传感器的自主移动机器人的探测系统

针对自主移动机器人沿墙导航过程,设计一种收发一体式超声波传感器与步进电机组成的探测系统.介绍此系统的结构和软硬件设计.实验总结超声波波束与目标物的入射角大小对测距稳定性的影响,提出搜寻离墙最近点的方法并应用于移动机器人自身位姿的矫正,且推广应用于移动机器人的环境探测.     

Fuzzy neural network-based real-time self-reaction of mobile robot in unknown environments

In this paper, a hybrid intelligent method including fuzzy inference and neural network is presented for real-time self-reaction of a mobile robot in unknown environments. A neural network with fuzzy inference (fuzzy neural network, FNN) presented can effectively improve the learning speed of the neural network. The method can be used to control a mobile robot based on the present motion situations of the robot in real-time; these situations include the distances in different directions between the obstacles and the robot provided by ultrasonic sensors, the target orientation sensed by a simple optical range-finder and the movement direction of the robot. Simulation results showed that the above method can quickly map the fuzzy relationship between the inputs and the output of the control system of the mobile robot.     

基于神经网络的移动机器人多传感器数据融合研究

针对单超声波的测距缺陷,采用多个超声波结合红外开关共同测距,提高整体测量精度;针对BP神经网络训练收敛速度慢,容易陷入局部极小值等缺点,加入动量-自适应因子来改进BP神经网络;将改进的BP应用于移动机器人传感器旅行家II号数据融合中,实践证明,经改进后的BP神经网络收敛精度高误差小,融合后的信息比未经融合的信息更精确。     

多传感器信息融合技术在移动机器人障碍探测中的应用

在移动机器人障碍探测中,需要实时准确的感知环境信息,而单一传感器仅能提供部分环境信息,对环境进行描述时存在局限性。文中提出采用红外传感器和超声波传感器相结合来感知环境信息,完成障碍物信息的采集,并利用自适应加权融合算法实现数据融合的方案。实验仿真结果表明,多传感器数据融合后比单一传感器所采集的数据更接近于真实值,波动性小,并且不易受外界环境的影响。该方案较好地满足了移动机器人障碍探测的需要,具有一定的有效性和实用性。     

Environment perception for a mobile robot using double ultrasonicsensors and a CCD camera

To move efficiently in an unknown or uncertain environment, a mobile robot must use observations taken by various sensors to construct information for path planning and execution. A reasonably accurate representation of the external world would also be very useful for robot self-localization. One of the merits of applying multiple sensors to a mobile robot is the enhancement of environment recognition. In this paper, the authors propose to use sensory information combined from double ultrasonic sensors and a CCD camera. They developed an algorithm based on a dual-transducer design to eliminate errors resulting from the beam opening angle of ultrasonic sensors. An extended discrete Kalman filter (EDKF) was designed to fuse raw sensory data and to reduce the influence of specular reflection of ultrasonic type transducers, thereby providing a more reliable representation for environment perception. Computer simulation, as well as practical experimental results demonstrate that this sensory system can provide useful and comprehensive environment perception for intelligent robotics