基于视觉引导和超声测距的运动目标跟踪和抓取

提出了装配机器人系统中一种基于视觉引导和超声测距的运动目标跟踪和抓取方法。介绍了运动目标的跟踪原理 ,采用图像雅可比矩阵进行机器人运动控制 ,跟踪运动的目标。利用视觉引导技术 ,获取目标在图像平面中的位置与方位 ,进行平面跟踪 ,然后引导超声波测距装置测取目标深度信息。实验结果验证了本文提出的这种方法的可行性和有效性     

Camera calibration using a genetic algorithm

An autonomous robot will have to detect moving obstacles online before it can plan its collision-free path, while navigating in a dynamic environment. The robot collects information about the environment with the help of a camera and determines the inputs for its motion planner through image analysis. The present article deals with issues related to camera calibration and online image processing. The problem of camera calibration is treated as an optimization problem and solved using a genetic algorithm so as to achieve minimum distorted image plane error. The calibrated vision system is then utilized for the detection and identification of the objects by analysing the images collected at regular intervals. For image processing, five different operations, such as median filtering, thresholding, perimeter estimation, labelling and size filtering, have been carried out. To show the effectiveness of the developed camera-based vision system, inputs of the motion planner of a navigating robot are calculated for two different cases. It is observed that online detection of the shapes and configurations of the obstacles is possible by using the vision system developed.     

Fiber-Grating-Based Vision System for Real-Time Tracking, Monitoring, and Obstacle Detection

There is a real need to develop a sensory system that can monitor and track the behavioral status of a person in real time while protecting his/her privacy. In addition, it is important to have the ability to detect stationary and moving objects in real time to support dynamic navigation needs for mobile robots. This paper describes the development of intelligent fiber-grating (FG)-based 3-D vision sensory system that enables real-time object detection, monitoring, and tracking. This system uses the richness and the strength of the vision while reducing the data load and computational cost by encoding the working space using a limited number of spatially interrelated 2-D laser spots. The sensor system generates the laser spots by projecting a coherent laser beam on two perpendicularly overlaid layers of FGs. The presence of a target within the visible operational view of the sensor disturbs the part of the projected laser spots' pattern where the target appeared. By calculating the displacement of the disturbed spots within the CCD image plane, the sensor system can detect, in a short time, an object/human and provide relevant information in terms of range, approximate shape, and position. To facilitate faster detection and real-time tracking, the author has developed two strategies that decompose the working space into zones and virtual planes     

基于环形红外阵列的移动机器人自动跟随系统

为了实现在室内空旷环境中跟随机器人对移动目标物的定位和动态跟踪,设计了一种基于环形红外阵列的移动机器人自动跟随系统。利用具有主动式环形大视场的测距罗盘作为环境感知传感器。测距罗盘由数个红外测距传感器组成周向阵列,实现对360°环向10～80 cm范围内移动目标物的二维定位,使跟随机器人可以快速确定其与移动目标物之间的距离和偏航角,实现对目标物的精准定位。依据目标物的位置信息并利用PD(proportiondifferentiation,比例-微分)控制器控制跟随机器人的移动,使跟随机器人保持与目标物的相对距离和相对角度,实现对移动目标物的自动跟随。在上位机操作界面可以实时显示跟随机器人的运动轨迹及其对周围未知环境的探测情况。通过实验证明了测距罗盘可以有效定位目标,满足机器人跟随移动目标物的设计要求。测距罗盘和自动跟随系统的可靠性较高,可以为机器人集群编队提供装置保障。     

基于视觉临场感的机器人遥操作系统

介绍了基于视觉临场感的机器人遥操作系统。该系统有机地把视觉临场感技术和机器人遥操作技术结合在一起,显著地提高了遥操作系统的性能。系统自主研制了视觉临场感系统,在普通的微机上实现了时分多路的立体视觉系统。自主研制了ＰＳＤ实时测量和位姿解算系统,实现了操作者的手部位姿的实时测量。深入地研究了机器人实时跟踪控制的算法,并在原有ＰＵＭＡ５６０机器人的基础上改造了核心控制软件,实现了机器人对操作者手部运动的     

基于LabVIEW的多通道视觉测速系统设计

目标运动速度与运动状态的快速预判是机器人避障、目标检测与跟踪的关键。经典的初级运动检测器（elementary motion detector,EMD）模型具有在局部范围内的速度矢量敏感特性,在此基础上结合波峰检测算法,提出一种动目标运动速度和运动状态的快速测速法。为验证所提方法的可行性和有效性,以线性排列的光敏传感器阵列为视觉检测单元,在LabVIEW开发环境中,利用雷赛SMC3380运动控制器和研华PCI-1747U数据采集卡,搭建了具有动目标运动控制及动目标信号采集功能的多通道视觉测速系统;通过多通道数据采集及动目标快速测速处理,实现了目标运动速度和运动状态的判别。实验结果表明：多通道视觉测速系统运行稳定,能够实现最大速度为80 mm/s（绝对误差小于±2 mm/s,相对误差小于±3%）,以及最大加速度为20 mm/s²的匀加速运动状态的动目标检测与判断。为机器人视觉感知器的动目标快速预判研究提供了新思路。     

Moving object detection and tracking in videos through turbulent medium

This paper addresses the problem of identifying and tracking moving objects in a video sequence having a time-varying background. This is a fundamental task in many computer vision applications, though a very challenging one because of turbulence that causes blurring and spatiotemporal movements of the background images. Our proposed approach involves two major steps. First, a moving object detection algorithm that deals with the detection of real motions by separating the turbulence-induced motions using a two-level thresholding technique is used. In the second step, a feature-based generalized regression neural network is applied to track the detected objects throughout the frames in the video sequence. The proposed approach uses the centroid and area features of the moving objects and creates the reference regions instantly by selecting the objects within a circle. Simulation experiments are carried out on several turbulence-degraded video sequences and comparisons with an earlier method confirms that the proposed approach provides a more effective tracking of the targets.     

一种基于卡尔曼预测的动态目标跟踪算法研究

针对视频序列中目标的跟踪,均值漂移算法和卡尔曼滤波器相结合的目标跟踪算法已经被提出,而在移动机器人上实现对机动目标的实时跟随时,机器人自身的运动引起目标在像平面的偏移不能被忽略,在详述了两者的关系的基础上,建立起以机器人一个周期内的运动作为输入量的状态方程,以卡尔曼滤波器的估计值作为均值漂移算法的启动点,均值漂移算法的最终收敛点作为每帧的跟踪结果,并以此收敛点替代滤波器的估计值,两种算法交替使用,互为补充.实验表明所提算法可以实现在室外环境下对动态目标的实时跟踪.     

Tracking and localization for omni-directional mobile industrial robot using reflectors

In this paper, an improved tracking and localization algorithm of an omni-directional mobile industrial robot is proposed to meet the high positional accuracy requirement, improve the robot's repeatability positioning precision in the traditional trilateral algorithm, and solve the problem of pose lost in the moving process. Laser sensors are used to identify the reflectors, and by associating the reflectors identified at a particular time with the reflectors at a previous time, an optimal triangular positioning method is applied to realize the positioning and tracking of the robot. The experimental results show that positioning accuracy can be satisfied, and the repeatability and anti-jamming ability of the omni-directional mobile industrial robot will be greatly improved via this algorithm. The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-018-0216-y     

Smooth pursuit eye movement system using artificial retina chip and shape memory alloy actuator

We developed a new active vision system using an artificial retina chip and the shape memory alloy actuator. A foveated CMOS retina chip for edge detection designed and fabricated for an image sensor of the developed system and the shape memory alloy actuator was used for mimicking the roles of the ocular muscles to track a desired target. Also, we proposed a new computational model that mimics the functional roles of our brain organs for generating the smooth pursuit eye movement. In our model, a neuromorphic model for the medial temporal cell generates motion energy, and the medial superior temporal cell is considered to generate an actuating signal so that the developed active vision system smoothly pursues the target with similar dynamics to the motion of our eyeball during the smooth pursuit. Experimental results show that the developed system successfully operates to follow the edge information of a moving object.     

基于动态运动基元的移动机器人路径规划

针对二维环境下移动机器人路径规划问题,提出一种基于动态运动基元(DMPs)的路径规划方法。该方法首先用手柄来控制机器人,记录机器人的运动轨迹,然后将记录的轨迹作为DMPs算法的学习样本,利用轨迹样本进行训练获得DMPs算法的模型参!,从而实现机器人的路径规划。当运动环境中有障碍物时,在已有学习基础上通过设计耦合因子规划出避障路径,在此基础上,改变机器人运动的目标位置,可以完成对新目标的泛化推广。仿真和实验结果表明,DMPs算法在移动机器人路径规划上具有可行性。     

未知环境下基于三次螺线Bug算法的移动机器人路径规划

研究了环境未知情况下的移动机器人实时路径规划问题,将Bug算法与基于滚动窗口的路径规划相结合,提出了一种改进的移动机器人路径规划方法。详细分析了三次螺线作为移动机器人跟踪路径所具有的各种优异的几何特性,定义路径光滑成本函数,利用三次螺线对滚动窗口内规划的路径光滑化,使得移动机器人易于跟踪所规划的路径,扩展了移动机器人的应用领域。最后对本文算法的收敛性和完备性予以证明。仿真实验验证了该方法的有效性。     

Bionic tracking method by hand & eye-vergence visual servoing

Animals rotate their eyes to gaze at the target prey, enhancing the ability of measuring the distance to the target precisely for catching it. These animals, visual tracking includes the triangular eye-vergence control and their body's motion control by visual servoing. The research aims to realize a bionic robot tracking performance, in which the body links moves together with eyes' view orientation. This paper proposed a hand & eye-vergence dual control system which included two feedback loops: an outer loop for conventional visual servoing to direct a manipulator toward a target object and an inner loop for active motion control of binocular cameras to change the viewpoint along with the moving object to give an accurate and broad observation. This research also foused on how to compensate a fictional motion of the target seen by camera images in an eye-in-hand system, where the camera was fixed on the end-effector and moved together with the hand motion. A robust motion-feedforward (MFF) recognition method is proposed to compensate the fictional motion of the target based on the manipulator's joint velocity, then the real motion of the target seen by camera images is extracted, which can improve the feedback image sensing unit to make the whole servoing system dynamically stable. The effectiveness of the proposed hand & eye-vergence visual servoing method is shown by tracking experiments using a 6-DoF robot manipulator and a 3-DoF binocular vision system.     

自主移动机器人视觉信息处理技术研究发展现状

视觉系统是自主移动机器人感知外界环境的主要手段之一.本文介绍了自主移动机器人视觉系统的基本组成以及不同类型的机器人视觉系统的主要特点,并结合自主移动机器人视觉系统的发展趋势,比较详细地介绍了基于 ASIC、DSP、FPGA、视觉芯片等技术的嵌入式视觉信息处理单元的主要特点及研究发展现状.本文最后提出了实现具有较强实用性的自主移动机器人视觉系统所需要解决的高实时性、通用性和适应性等若干关键问题.     

基于并联机器人的包装分拣系统设计

目的针对我国食品生产和包装存在的效率低、分拣精度不高等问题,基于并联机器人设计一种包装分拣控制系统。方法根据机器人自动分拣系统的结构,采用一种基于时间和工件位置的图像去重复算法,以去掉重复信息。为了提高抓取精度,基于PID算法设计一种位置跟踪控制器,能够判断物体位置并实时调整并联机器人末端执行器,以实现目标物体的动态跟踪和抓取。结合工业控制机和运动控制卡搭建控制系统,并进行实验研究。结果实验过程中最快分拣速度可达到120次/min,漏抓率为0,误抓率小于0.2%。结论所述控制系统具有较高的稳定性和准确性,可满足实时性要求。     

一种新的红外目标跟踪方法

一般的Snake模型用于目标跟踪时存在一些问题,如要求初始控制点位置非常接近于真实 轮廓、不能可靠跟踪快速运动目标、对目标的运动规律有许多约束条件等。在继承所提出的Auto-Snake模型跟踪算法优点的基础上,进一步采用最小二乘估计预测器对目标的位置进行预测,放宽对运动规律的约束,可以实现对快速运动(大位移)的目标的自动跟踪。     

基于无标定全局视觉反馈的三维运动目标的图像跟踪方法

研究机器人在摄像机图像平面上对三维运动目标的跟踪方法。在摄像机模型未知及机器人与摄像机关系没有标定时 ,利用雅可比矩阵 ,可直接从图像上观察到的机器人手爪和运动目标之间的位置误差 ,计算出机器人手爪为消除这个误差的期望运动。并给出雅可比矩阵形式的推导过程     

Image tracking of motorcycles and vehicles on urban roads and its application to traffic monitoring and enforcement

Abstract

Image tracking has increasingly gained attention for use in vision‐based traffic monitoring and surveillance applications. For many cities in Asia countries, it is desirable to detect multiple motorcycles as well as cars for urban traffic monitoring and enforcement. In this paper, a novel contour initialization and tracking algorithm is presented to track multiple motorcycles and vehicles at any position on the roadway. This method has the capability to detect moving vehicles of various sizes and to generate their initial contours for image tracking. The proposed method is not constrained by lane boundaries or vehicle size. To track vehicles on roadways, dynamic models are designed to predict the horizontal and vertical positions of vehicle contours. A Kalman filter is designed to update the prediction based on real‐time image measurement. Practical experimental studies using video clips are presented to evaluate the performance of the proposed method. Traffic parameters such as traffic flow, vehicle speeds and traffic density are obtained with satisfactory accuracy.     

基于双曲调频距离误差的目标跟踪修正算法

双曲调频信号的多普勒不变性可使运动目标匹配滤波输出的能量损失达到最小，在运动目标检测与参数估计中具有独特优势，已广泛应用于新型主动声呐。然而其多普勒不变性在提高检测能力的同时，会引入目标距离估计误差，从而影响主动声呐跟踪性能。文章在分析双曲调频信号距离估计误差的基础上，提出了目标跟踪算法的误差修正方法，通过将距离估计误差公式与传统观测方程及滤波算法进行融合，实现目标跟踪算法的误差补偿，显著提高了算法的跟踪性能，尤其是对快速运动目标的跟踪性能。     

Using short-time Fourier transform and wavelet packet filter banksfor improved frequency measurement in a Doppler robot tracking system

Previous research has shown that an ultrasonic tracking system using the Doppler effect can potentially track high-speed robot motion very accurately. However, ultrasound energy that is reflected by obstacles in the robot workspace can cause significant distortions in the frequency measurement. To reduce the distortions, a novel method for frequency measurement is described in this paper. This uses the short-time Fourier transform (STFT) to estimate the frequency of the interference signal. Then, the estimated frequencies are analyzed with an adaptive filter constructed with wavelet packet filter banks. Results are given that demonstrate great improvements in frequency measurement