Straight‐Line Tracking Control of an Agricultural Vehicle with Finite‐Time Control Technique

For the agricultural vehicle straight‐line tracking system, three control algorithms based upon the finite‐time control technique have been proposed to force the vehicle to track a straight line. Without considering the lumped disturbance, a backstepping‐like finite‐time state‐feedback controller is first developed. On this basis, an adaptive state‐feedback controller in conjunction with integral sliding mode is further developed in the presence of the lumped disturbance. Finally, a sliding mode disturbance observer is given to estimate the lumped disturbance, and the composite control scheme is presented. Under the composite controller, the lumped disturbance can be compensated and thus the disturbance rejection property has been significantly improved. Simulation results verify the proposed control algorithms.     

基于分层光流的煤矿井下运动目标跟踪算法

针对煤矿井下视频序列高噪声、运动目标繁多、目标交错等特点,提出了一种基于分层光流法的矿井运动目标跟踪算法。首先对相邻两帧视频序列采用帧差法确定多个初始目标跟踪模版;然后采用SUSAN角点检测提取模版内的特征点;最后运用改进的分层光流法进行目标检测和跟踪,并在跟踪过程中对模版进行更新。该算法实现了煤矿井下多目标运动物体的稳定跟踪,并能解决目标部分遮挡问题。实验和仿真结果证实了该算法的有效性。     

一种智能寻迹与搬运机器人的控制系统设计

提出寻迹与搬运机器人的一种智能控制系统设计;该系统主要由单片机、传感器和执行舵机组成;通过分析直行、弯道与取物等工作模式,建立相应的舵机驱动控制;传感器将检测到的路线和工件信号传送给单片机进行处理;按照不同的优先级别,由单片机发出脉冲信号,控制舵机的速度与方向,完成抓取、转运工件的任务;实验结果表明:多路传感器的信息融合能有效识别寻迹路径,确定优先级别的控制;舵机的驱动控制能满足寻迹与搬运的要求;系统设计简单,实用可靠,具有良好的开放性与扩展性.     

太阳能LED路灯控制系统的设计

设计了一套基于STC12单片机的太阳能LED路灯控制系统,系统采用变步长的电导增量法跟踪太阳能电池板最大功率点,充分利用太阳能电池板的能量,对铅酸蓄电池充电。同时实时监测铅酸蓄电池的电压防止蓄电池过充、过放等现象;对LED路灯采用多段式的恒流控制,通过环境照度的监测控制LED路灯在不同电流强度下工作,以增强LED路灯的使用寿命,实现节约用电的目的。     

Android智能手机的云服务应用研究

云计算的应用目标并不仅局限于PC,随着移动互联网的蓬勃发展,基于手机等移动终端的云服务已成为IT行业炙手可热的新业务发展模式。本文基于Openmobster搭建移动云计算环境,并利用Android智能手机作为终端来访问云端服务器资源,以数据传输的事务处理为应用背景,采用c／s模式和B／S模式相结合的方式,建立了云服务下移动智能终端信息采集和处理的基础架构,并根据此架构初步实现了追踪定位的功能。该方法通过无线网络连接,利用服务器端与手机客户端的即时通信,实现了为Android智能手机提供云推送和云同步的服务。     

基于PSO算法的运动目标跟踪研究

提出一种基于PSO的运动目标跟踪方法,并在TMS320DM642上实现.该方法首先针对采集到图像的Y分量通过帧间差分和背景差分相结合的方法建立背景模型,然后检测出前景运动目标,接着通过前景运动目标初始化目标模板,再对目标模板和待跟踪视频图像分别进行两次金字塔降采样,降低目标模板和待跟踪视频图像的分辨率.在顶层金子塔上采用粒子群优化算法对跟踪目标进行粗定位,在中间层和底层金字塔上采用钻石搜索方法对跟踪目标进行精确定位.在目标跟踪的过程中,目标模板随运动目标的变化而不断更新,实现对目标的实时连续性跟踪.该方法可以有效降低计算复杂度,提高搜索效率.     

嵌入式应用中接收GSM短消息的两种方法

介绍了GSM短消息中的PDU编码方式和基本AT指令,对SIM卡中的短消息存储顺序作出说明。重点介绍了在嵌入式应用中,利用查询方式和中断方式收发GSM短消息的两种基本方法。     

基于并行群体模拟退火算法的蛋白质折叠研究

蛋白质折叠研究对于揭示蛋白结构和功能关系,进而了解相关疾病的致病机理意义重大。蛋白质折叠已被证明是 NP-完全问题。本文针对蛋白质折叠研究中的能量最小化问题,提出了一种新的并行群体模拟退火算法（Parallel Group Simulated Annealing,PGSA）及其改进型算法（PGSA_1/K)。该算法使用了降温因子加速收敛精度,并采用 MPI 消息传递并行编程技术加快蛋白质结构空间搜索以及能量最小化寻找速度。以 Met_Enkephalin 蛋白为对象的计算机模拟仿真结果表明,我们提出的算法及其改进型有很好的扩展性,可以高效搜索蛋白结构空间,从而找到相关蛋白的最小能量结构。     

Three-dimensional automated nanoparticle tracking using Mie scattering in an optical microscope

The forward scattering of light in a conventional inverted optical microscope by nanoparticles ranging in diameter from 10 to 50nm has been used to automatically and quantitatively identify and track their location in three-dimensions with a temporal resolution of 200ms. The standard deviation of the location of nominally stationary 50-nm-diameter nanoparticles was found to be about 50nm along the light path and about 5nm in the plane perpendicular to the light path. The method is based on oscillating the microscope objective along the light path using a piezo actuator and acquiring images with the condenser aperture closed to a minimum to enhance the effects of diffraction. Data processing in the time and spatial domains allowed the location of particles to be obtained automatically so that the technique has potential applications both in the processing of nanoparticles and in their use in a variety of fields including nanobiotechnology, pharmaceuticals and food processing where a simple optical microscope maybe preferred for a variety of reasons.     

Multi-target tracking on confidence maps: An application to people tracking

We propose a generic online multi-target track-before-detect (MT-TBD) that is applicable on confidence maps used as observations. The proposed tracker is based on particle filtering and automatically initializes tracks. The main novelty is the inclusion of the target ID in the particle state, enabling the algorithm to deal with unknown and large number of targets. To overcome the problem of mixing IDs of targets close to each other, we propose a probabilistic model of target birth and death based on a Markov Random Field (MRF) applied to the particle IDs. Each particle ID is managed using the information carried by neighboring particles. The assignment of the IDs to the targets is performed using Mean-Shift clustering and supported by a Gaussian Mixture Model. We also show that the computational complexity of MT-TBD is proportional only to the number of particles. To compare our method with recent state-of-the-art works, we include a postprocessing stage suited for multi-person tracking. We validate the method on real-world and crowded scenarios, and demonstrate its robustness in scenes presenting different perspective views and targets very close to each other.