无人机导航监控系统设计与实现

针对传统模拟表盘式导航监控系统存在人工估算飞机位置偏差大、模拟表盘读数精度低、人机交互性差等问题,提出了基于数字地图、信号滤波处理和自动航线规划的无人机导航监控系统设计方案,给出了设计原理、系统组成以及实现方法.     

无人直升机着陆控制的视觉图像特征处理算法

基于视觉的无人直升机着陆是无人直升机着陆控制中的主要发展方向,视觉图像处理算法将直接影响无人直升机姿态估计以及着陆控制精度.提出了一种应用于无人直升机着陆控制的视觉图像特征处理算法,对目标灰度图像进行阈值处理,边界跟踪,利用凸四边形几何特点提取特征点,最后将所有特征点标记出来.实验结果显示提出的算法即能满足实时处理速度要求,也能满足较高的特征点定位精度要求.这一方法可用于无人直升机着陆控制的相对位置姿态估计.     

移动机器人视觉导航控制研究

该文研究了移动机器人视觉导航的控制问题。针对导航中的图像畸变以及视野有限易造成导航线丢失等问题,提出了一种简单的单目视觉目标定位算法和一种新的控制策略。在导航时,首先利用定位算法精确地获取地面目标的深度信息,然后控制机器人沿一系列切线方向平滑接近导航线(或目标),并根据实施控制的时间间隔控制速度,以保证机器人视野中导航线(或目标)不丢失。实际的应用证明了该定位算法和策略的有效性。     

基于三维模型的交通场景视觉监控

视觉监控是计算机视觉研究的前沿方向.动态场景视觉监控就是利用计算机视觉和人工智能的理论和方法.通过对摄像机拍录的图像序列进行自动分析来对场景中的运动物体进行定位、跟踪和识别,并对物体的运动行为作出判断或者解释,达到监控的目的.本文结合交通场景监控这一特定任务,实现一个包括摄像机标定、模型可视化、运动车辆的姿态优化与定位、跟踪预测、基于轨迹分析的行为理解等功能算法的交通场景视觉监控系统.从算法和实现的角度出发，文章对系统中各个功能模块进行了较为详细的描述与讨论.     

智能车跟随系统开发

开发了一种基于STM32视觉导航的目标跟随小车智能控制系统,实现了对特定目标物体的快速识别与实时准确跟随.使用OV7670图像传感器采集目标物图像信息,对图像进行灰度化、降噪、取反等处理后,通过亚像元定位技术的质心法获取目标物坐标位置,为智能车提供方向导航,跟随过程中的画面实时发送至上位机.结果表明:小车在直行和转向跟踪实验中表现良好,跟随系统具有良好的跟踪效果,可实现对目标物的实时准确跟随.     

基于空间尺度寻优的公共信息标志的主动搜索

为了使“福娃机器人”能够在机场候机楼中自主导航,以公共信息标志为导航路标,研究公共信息标志的搜索与检测问题,提出了一种基于视觉时空多尺度信息的标志搜索与检测方法。利用公共信息标志形状的先验信息,在空间大尺度下对公共信息标志快速搜索。当公共信息标志在图像上呈现模糊、标志部分信息缺失、标志粘连等现象时,根据时空相关性自动进行空间尺度变化、寻找最优空间尺度完成公共信息标志的二次搜索与检测。实验结果证明了该方法的快速性和有效性。     

基于方向引导优化的视觉导航方法

为解决主动视觉导航在复杂路况条件下精度较差的问题,提出了一种基于方向引导优化的主动视觉导航参量计算方法。首先,建立了车辆物理坐标系与视觉图像坐标系的变换方程,通过Canny算子对视频图像进行初步的车道边缘线和道路标志线检测;接着,基于方向引导优化有效降低了阴影、积水等杂波对检测性能的干扰,并通过阈值优化的广义Hough变换实现车道线的内外边缘及道路标志线的精确检测;最后,基于检测结果计算出用于导航的中心引导线、偏离角度、距离等参量。实验结果表明,该方法能够有效且精确地获取主动导航系统的偏移参量。     

基于视觉AGV的行驶状态数字化控制技术的研究

基于视觉导航的自动导航小车(AGV)依靠车载CCD摄像机获取车辆周围的图像信息,再经车载计算机对获取的图像信息进行分析得出控制AGV行驶的控制信息,从而便车辆在无人控制下按设定的路径的行驶状态自动行驶;提出将AGV行驶的速度、定时停车、停车等行驶状态信息进行数字化并用条形码进行表示的方法实现对AGV行驶状态的控制,给出控制信息数字化和条形码编制、扫描、识别的算法;利用计算机模拟AGV实际的运行状态对上述方法进行仿真,仿真结果表明,该方法具有识别算法简单、易于进行定性和定量控制、使用灵活、鲁棒性好的特点.     

卡尔曼滤波焊缝跟踪控制

在视觉传感的电弧自动焊接过程中,需要根据视觉信息来控制电弧准确地跟踪焊缝.由于强烈的弧光干扰,使得从焊接区图像中直接提取电弧与焊缝的偏差信息十分困难.为此提出一种利用熔池图像质心和卡尔曼滤波来间接获取电弧与焊缝偏差的方法.选择熔池图像质心作为状态向量,建立基于图像质心的状态方程和焊缝位置测量方程.利用卡尔曼滤波消除过程噪声和测量噪声的影响,通过对熔池图像质心的状态估计,准确获取焊缝位置以及电弧与焊缝之间的偏差量,为自动焊接过程的焊缝跟踪控制提供准确信息.焊接试验结果表明,利用卡尔曼滤波方法可有效降低过程噪声和测量噪声的影响,从而提高焊缝跟踪控制精度.     

基于虚拟导航线的农业机器人精确视觉导航方法

针对农田、野外环境中无人工标记情况下的导航问题，提出了一种基于虚拟导航线的农业机器人精确视觉导航方法。该方法不需要铺设导航线或者路标即可引导机器人行走直线。首先，根据需求确定需要跟踪的目标区域，之后控制机器人调整方向直到目标移至视野中央；其次，根据机器人和目标的位置确定参照目标，并依据两个目标的位置确定虚拟导航线；然后，动态更新导航线，并结合虚拟定标线和虚拟导航线确定偏移角度和偏移距离；最后，利用偏移参数构建模糊控制表，并以此实现对机器人旋转角度和行走速度的调整。实验结果表明，该算法能较为精确地实现对导航路线的识别，进而利用模糊控制策略使机器人沿直线向目标行走，且导航精度在10 cm以内。     

Trajectory tracking for an autonomous airship using fuzzy adaptive sliding mode control

We present a novel control approach for trajectory tracking of an autonomous airship.First,the dynamics model and the trajectory control problem of an airship are formulated.Second,the sliding mode control law is designed to track a time-varying reference trajectory.To achieve better control performance,fuzzy adaptive sliding mode control is proposed in which the control gains are tuned according to fuzzy rules,and an adaptation law is used to guarantee that the control gains can compensate for model uncertainties of the airship.The stability of the closed-loop control system is proven via the Lyapunov theorem.Finally,simulation results illustrate the effectiveness and robustness of the proposed control scheme.     

自治飞艇直接自适应模糊路径跟踪控制

针对具有模型不确定和未知外部干扰的自治飞艇, 提出了直接自适应模糊路径跟踪控制方法. 该方法由路径跟踪控制和自适应模糊控制两部分组成. 首先基于飞艇的平面运动模型设计路径跟踪控制律, 包括制导律计算、偏航角跟踪和速度控制3 部分; 然后构造直接自适应模糊控制器逼近路径跟踪控制律中的不确定项. 稳定性分析证明所设计的控制律能使飞艇跟踪给定的期望路径, 跟踪误差收敛到原点的小邻域内. 仿真结果验证了所提出方法的有效性.

     

Fuzzy Policy Reinforcement Learning in Cooperative Multi-robot Systems

A multi-agent reinforcement learning algorithm with fuzzy policy is addressed in this paper. This algorithm is used to deal with some control problems in cooperative multi-robot systems. Specifically, a leader-follower robotic system and a flocking system are investigated. In the leader-follower robotic system, the leader robot tries to track a desired trajectory, while the follower robot tries to follow the reader to keep a formation. Two different fuzzy policies are developed for the leader and follower, respectively. In the flocking system, multiple robots adopt the same fuzzy policy to flock. Initial fuzzy policies are manually crafted for these cooperative behaviors. The proposed learning algorithm finely tunes the parameters of the fuzzy policies through the policy gradient approach to improve control performance. Our simulation results demonstrate that the control performance can be improved after the learning.     

室内无人飞艇导航系统的研究与仿真

根据室内飞艇导航应用的特点,介绍了超宽带(UWB)导航系统在室内无人飞艇自主飞行系统中的应用方法,根据室内场所等条件的要求,建立了室内飞艇系统的导航模型,以Matlab/Simulink为平台,对UWB进行了实时导航的仿真实验.实验结果不仅证明该导航方法具有较高的导航精度,而且为进一步研究室内飞行器导航系统开辟了一条比...     

Distributed fuzzy discrete event system for robotic sensory information processing

Abstract: This paper presents a novel intelligent sensory information processing technique using a fuzzy discrete event system (FDES) for robotic control. The proposed method combines the predictive control approach of a discrete event system with the approximate reasoning aspect of fuzzy logic. It develops a supervisory control strategy for behavior-based robotic control using distributed FDES. The application of distributed FDES eliminates the formation of complex fuzzy predicates and a large fuzzy rule-base. The FDES-based approach also provides means for analyzing behavior-based decision-making using the observability and controllability of an FDES. The observability of an FDES describes uncertainties in sensory data, and the controllability of an FDES exploits uncertain state transitions in a dynamic environment. Comprehensive experiments on behavior-based mobile robot navigation are presented to authenticate the performance of the proposed methodology.     

Visual station keeping for floating robots in unstructured environments

This paper describes the use of vision for navigation of mobile robots floating in 3D space. The problem addressed is that of automatic station keeping relative to some naturally textured environmental region. Due to the motion disturbances in the environment (currents), these tasks are important to keep the vehicle stabilized relative to an external reference frame. Assuming short range regions in the environment, vision can be used for local navigation, so that no global positioning methods are required. A planar environmental region is selected as a visual landmark and tracked throughout a monocular video sequence. For a camera moving in 3D space, the observed deformations of the tracked image region are according to planar projective transformations and reveal information about the robot relative position and orientation w.r.t. the landmark. This information is then used in a visual feedback loop so as to realize station keeping. Both the tracking system and the control design are discussed. Two robotic platforms are used for experimental validation, namely an indoor aerial blimp and a remote operated underwater vehicle. Results obtained from these experiments are described.     

机器人视觉跟踪轨迹的分级规划方法

针对跟踪轨迹规划对于确保得到连续光滑的跟踪运动的重要性，提出了两级视觉跟踪轨迹规划方法。第一阶段在图像平面上规划运动轨迹，在图像平面上得到的离散规划点映射到机器人关节空间。第二阶段在机器人关节空间中用三次样条函数来连接这些离散点。为了满足实时控制的要求，在图像处理过程中采用窗口技术并抽取边缘特征。建立用于跟踪两维平面运动物体(如随运输带运动的物体)的机器人视觉跟踪控制系统。实验结果表明，跟踪误差渐近地减小到允许的数值范围，所提出的跟踪轨迹规划方法是有效的。     

Adaptive Fuzzy Backstepping Tracking Control for Flexible Robotic Manipulator

In this paper, an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator system. The considered system contains unknown nonlinear function and actuator saturation. Fuzzy logic systems (FLSs) and a smooth function are used to approximate the unknown nonlinearities and the actuator saturation, respectively. By combining the command-filter technique with the backstepping design algorithm, a novel adaptive fuzzy tracking backstepping control method is developed. It is proved that the adaptive fuzzy control scheme can guarantee that all the variables in the closed-loop system are bounded, and the system output can track the given reference signal as close as possible. Simulation results are provided to illustrate the effectiveness of the proposed approach.      

Cooperative passers-by tracking with a mobile robot and external cameras

In this paper, we present a cooperative passers-by tracking system between fixed view wall mounted cameras and a mobile robot. The proposed system fuses visual detections from wall mounted cameras and detections from a mobile robot–in a centralized manner–employing a “tracking-by-detection” approach within a Particle Filtering strategy. This tracking information is then used to endow the robot with passers-by avoidance ability to facilitate its navigation in crowds during the execution of a person following mission. The multi-person tracker’s ability to track passers-by near the robot distinctively is demonstrated through qualitative and quantitative off-line experiments. Finally, the designed perceptual modalities are deployed on our robotic platform, controlling its actuators via visual servoing techniques and free space diagrams in the vicinity of the robot, to illustrate the robot’s ability to follow a given target person in human crowded areas.