Robust Adaptive Neural Control for a Class of Time‐Varying Delay Systems with Backlash‐like Hysteresis Input

This paper proposes a robust adaptive dynamic surface control (DSC) scheme for a class of time‐varying delay systems with backlash‐like hysteresis input. The main features of the proposed DSC method are that 1) by using a transformation function, the prescribed transient performance of the tracking error can be guaranteed; 2) by estimating the norm of the unknown weighted vector of the neural network, the computational burden can be greatly reduced; 3) by using the DSC method, the explosion of complexity problem is eliminated. It is proved that the proposed scheme guarantees all the closed‐loop signals being uniformly ultimately bounded. The simulation results show the validity of the proposed control scheme.     

基于深度图像的人体运动姿态跟踪和识别算法

由于人体运动的复杂性,现有基于低质量深度图像的三维立体姿态跟踪和识别 方法的准确性较低、鲁棒性较差。针对低质量深度图像的人体运动姿态和识别问题,本文设 计了一种基于三步搜索算法的人体运动姿态的跟踪和识别方法。该方法首先对获取的深度信 息进行分析,从而判定人体轮廓;然后通过基于深度图像的骨骼跟踪方法跟踪特定骨骼点, 并采用三步搜索算法进行运动估计,跟踪获取人体运动轨迹;最后利用获取的骨骼点坐标实 现人体运动姿态的识别。实验结果表明,该算法克服光照影响的鲁棒性较强,且能有效地提 高人体运动姿态跟踪与识别的准确性。     

机载跟踪器的逃逸目标图像快速识别模型仿真

机载跟踪器进行逃逸目标识别跟踪的过程中,目标往往是高速移动的,为了逃逸跟踪,运动的速度和方向具有较大的突变性,与跟踪器之间会形成较大的跟踪距离差.传统的视觉方法为了弥补这种距离差,通过减少采集图像的样本,以提高跟踪的准确性,但是一旦样本数量过少,将会导致识别跟踪的准确性降低.提出基于高斯分布的动态逃逸目标识别跟踪方法.对跟踪目标图像进行归一化处理,获取与数据库中的样本图像具有同样的尺寸和分辨率的图像.计算动态目标图像的形心,根据高斯分布原理建立动态目标的识别跟踪模型,并对模型中的相关参数进行及时更新,保证了动态目标识别跟踪的及时性和准确性.实验结果表明,利用改进算法能够有效提高动态目标识别跟踪的准确性,缩短了识别跟踪的时间.     

A Saturating Extension of an Output Feedback Controller for Internally Damped Euler‐Lagrange Systems

In this research, a novel extension of the passivity‐based output feedback trajectory tracking controller is developed for internally damped Euler‐Lagrange systems with input saturation. Compared with the previous output feedback controllers, this new design of a combined adaptive controller‐observer system will reduce the risk of actuator saturation effectively via generalized saturation functions. Semi‐global uniform ultimate boundedness stability of the tracking errors and state estimation errors is guaranteed by Lyapunov stability analysis. An application of the proposed saturated output feedback controller is the stabilization of a nonholonomic wheeled mobile robot with saturated actuators towards desired trajectories. Simulation results are provided to illustrate the efficiency of the proposed controller in dealing with the actuator saturation.     

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。     

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.     

Particle filters and occlusion handling for rigid 2D–3D pose tracking

In this paper, we address the problem of 2D–3D pose estimation. Specifically, we propose an approach to jointly track a rigid object in a 2D image sequence and to estimate its pose (position and orientation) in 3D space. We revisit a joint 2D segmentation/3D pose estimation technique, and then extend the framework by incorporating a particle filter to robustly track the object in a challenging environment, and by developing an occlusion detection and handling scheme to continuously track the object in the presence of occlusions. In particular, we focus on partial occlusions that prevent the tracker from extracting an exact region properties of the object, which plays a pivotal role for region-based tracking methods in maintaining the track. To this end, a dynamical choice of how to invoke the objective functional is performed online based on the degree of dependencies between predictions and measurements of the system in accordance with the degree of occlusion and the variation of the object’s pose. This scheme provides the robustness to deal with occlusions of an obstacle with different statistical properties from that of the object of interest. Experimental results demonstrate the practical applicability and robustness of the proposed method in several challenging scenarios.