基于深度卷积神经网络的视觉里程计研究

视觉里程计利用视频信息来估计相机运动的位姿参数，实现对智能体的定位。传统视觉里程计方法需要特征提取、特征匹配/跟踪、外点剔除、运动估计、优化等流程，解算非常复杂，因此，提出了基于卷积神经网络的方法来实现端对端的单目视觉里程计。借助卷积神经网络对彩色图片自动学习提取图像帧间变化的全局特征，将用于分类的卷积神经网络转化为帧间时序特征网络，通过三层全连接层输出相机的帧间相对位姿参数。在KITTI数据集上的实验结果表明，提出的Deep-CNN-VO模型可以较准确地估计车辆的运动轨迹，证明了方法的可行性。在简化了复杂模型的基础上，与传统的视觉里程计系统相比，该模型的精度也有所提高。     

基于移动锚节点与多级通信的三维传感器网络节点自定位算法研究

在基于移动锚节点的三维传感器网络节点自定位算法SNLSFA(Sensor Node Localization Scheme based on Flying Anchors)的基础上,提出了一种新的基于移动锚节点与多级通信的三维传感器网络节点自定位算法SNLSFAMC(Sensor Node Localization Scheme based on Flying Anchors and Multi-level Communication)。首先由移动锚节点提供3个或4个辅助定位点,再由辅助定位点得到两条非平行线段,然后过线段中点分别做垂直于线段的平面,经两平面相交后得到一条经过待定位节点的直线,最后利用辅助定位点与待定位节点之间的距离作为通信半径即可得到待定位节点的位置。仿真结果表明,与SNLSFA相比,在相同锚节点数量下,SNLSFAMC提高了定位精度,且在相同定位精度下,SNLSFAMC降低了对锚节点数量的需求,提高了算法的响应时间。     

基于信号相位搜索的WSN节点定位算法

节点定位是无线传感器网络（wireless sensor network,WSN）研究的热点问题之一,基于信号相位信息与物理距离间的关系提出了基于信号相位搜索的WSN节点定位算法。该算法首先根据节点间信号相位信息,基于余弦相似性算法原理构建目标函数,将WSN节点定位问题转换为目标函数最优解搜索问题;然后基于质心定位算法原理确定搜索初始像素单元;最后利用梯度下降法替代逐像素单元的遍历搜索,在不影响定位精度情况下进一步提高定位效率,减小定位功耗。仿真实验结果表明,该算法的各项指标良好,适用于WSN的节点定位。     

面向移动节点定位的传感器网络动态休眠调度机制

由于能量受限的传感器节点一般多采用低功耗的工作方式,即在休眠状态和唤醒状态之间切换,因此,当对移动节点进行定位时,锚节点可能会因为处于休眠状态而没有响应移动节点的定位请求,从而导致定位失败.提出一种基于预唤醒的动态休眠调度机制P-SWIM,该机制提前通知移动节点周边的锚节点进入全勤的工作方式,而网络内其他锚节点则仍然处于低功耗的工作方式.通过P-SWIM,目标节点能够有效地维持足够高的锚节点连通度,从而保证了定位的成功率和精度.实验结果表明,移动节点定位方法采用P-SWIM相比于采用静态休眠调度机制(如RIS和GAF)能够显著地提高定位性能,且P-SWIM引入的运行功耗也是3种机制中最低的,比RIS和GAF最多可节省47.6%和60.2%的功耗.     

无线传感器网络节点自身定位算法研究

无线传感器网络中节点自身位置信息是实现其应用的最重要因素之一.针对节点自身定位的研究很多,但很大一部分都集中在算法的改进和新算法的开发上,很少给出纵向直观的仿真效果比较.研究选取无需测距算法中4种典型的算法,给出它们在不同参数下的仿真定位效果图,对于工程人员根据实际选取最优算法有很好的借鉴作用.在此基础上,利用曲线拟合...     

Shape Morphing-Based Control of Robotic Visual Servoing

We present an approach for controlling robotic interactions with objects, using synthetic images generated by morphing shapes. In particular, we attempt the problem of positioning an eye-in-hand robotic system with respect to objects in the workspace for grasping and manipulation. In our formulation, the grasp position (and consequently the approach trajectory of the manipulator), varies with each object. The proposed solution to the problem consists of two parts. First, based on a model-based object recognition framework, images of the objects taken at the desired grasp pose are stored in a database. The recognition and identification of the grasp position for an unknown input object (selected from the family of recognizable objects) occurs by morphing its contour to the templates in the database and using the virtual energy spent during the morph as a dissimilarity measure. In the second step, the images synthesized during the morph are used to guide the eye-in-hand system and execute the grasp. The proposed method requires minimal calibration of the system. Furthermore, it conjoins techniques from shape recognition, computer graphics, and vision-based robot control in a unified engineering amework. Potential applications range from recognition and positioning with respect to partially-occluded or deformable objects to planning robotic grasping based on human demonstration.     

中央民族大学信息工程学院，北京100081

分析网络化感知系统节点定位问题的特殊性,针对深空探测环境未知的问题,提出利用全景图像重合度来修正信号衰减模型,提高测距精度;提出一种修正的高精度节点自主定位算法来解决多移动节点协同定位问题,该算法是把切圆法引入到基于全景图片重合度的RSSI修正定位方法中。当多个感知节点定位时,根据视距近似原则选择定位锚节点来进行H-CM算法,仿真结果表明该定位方案可以有效提高感知节点的定位精度。     

A Color Vision-Based Lane Tracking System for Autonomous Driving on Unmarked Roads

This work describes a color Vision-based System intended to perform stable autonomous driving on unmarked roads. Accordingly, this implies the development of an accurate road surface detection system that ensures vehicle stability. Although this topic has already been documented in the technical literature by different research groups, the vast majority of the already existing Intelligent Transportation Systems are devoted to assisted driving of vehicles on marked extra urban roads and highways. The complete system was tested on the BABIECA prototype vehicle, which was autonomously driven for hundred of kilometers accomplishing different navigation missions on a private circuit that emulates an urban quarter. During the tests, the navigation system demonstrated its robustness with regard to shadows, road texture, and weather and changing illumination conditions.     

贴片机视觉检测中角度计算的一种高效算法

视觉检测是半导体器件封装贴片设备的核心技术之一。文中提出了半导体芯片视觉检测中角度检测的一种有效算法。该算法通过提取芯片边缘点的坐标点集扣拟合直线参数来计算芯片的角度。文章解释了角度检测的含义，介绍了算法的基本思想和算法步骤，并给出了实验数据。实验结果表明，该算法具有较高的准确度和处理速度，满足了实时处理的要求。     

Vision-Based Navigation for an Electric Wheelchair Using Ceiling Light Landmark

This paper presents an autonomous wheelchair system with the capability of self-location and obstacle avoidance. The wheelchair is equipped with two TV cameras that are used for self-location and obstacle avoidance, respectively. In this system, the fluorescent ceiling lights are chosen as landmarks since they can be easily detected and do not require an additional installation. A recognition procedure of landmarks is described by which the desired landmark images in the navigational environment can be retrieved. A self-location technique using ceiling light landmarks is proposed. Using this self-location function, the wheelchair can locate itself in a world coordinate system. The path planning based on landmark and the method of generating a control scheme are presented so that the wheelchair is capable of navigating along any path from start position to goal position. A low cost and high-speed vision system for the detection and avoidance of obstacle is developed and the principal of obstacle avoidance is introduced. A number of navigation experiments are conducted for the wheelchair in an indoor environment. The experimental results indicate the effectiveness of the wheelchair system.