井下移动机器人智能视觉避障研究

针对现有井下移动机器人避障方法在面对井下复杂障碍物时不能准确检测障碍物位置信息,对井下非线性障碍物不能准确进行避障控制等问题,提出了一种基于模糊控制的井下移动机器人智能视觉避障方法。首先采用双目立体视觉模组作为障碍物检测传感器,感知井下环境信息,实时检测障碍物分布情况,并构建占据栅格地图。然后通过八叉树结构模型构建三维点云,使用树状结构对点云数据进行结构化描述,并将其映射到占据栅格地图中,得到障碍物的区域分布情况。最后采用模糊控制策略对实时检测到的障碍物在占据栅格地图中的分布情况进行处理,将当前时刻障碍物在占据栅格地图中的分布情况和移动机器人运行速度作为模糊控制器的输入变量,通过模糊控制算法计算下一时刻移动机器人的转向角度和加速度,从而实现井下移动机器人的智能避障控制。根据移动机器人实际占据空间,设计外接包围盒进一步稳定控制算法,结合避障策略进行智能避障,避免移动机器人与障碍物发生碰撞。实验结果表明,该方法能够准确对井下障碍物分布情况进行描述,使移动机器人能够根据所设计的模糊控制规则准确自主地进行避障操作,从而实现自适应运动。     

智能轮椅室内避障导航及仿真实现

关于智能轮椅路径识别问题,如何采集外界障碍物信息,以及迅速的做出判断是智能轮椅进行室内避障导航的关键.针对轮椅受路面粗超度,轮胎变形,和结构变彤等的影响,整个系统表现为高度的非线性和不确定性.为解决上述问题,提出在智能轮椅中安装超声、红外传感器,利用模糊逻辑算法处理障碍物信息进行室内避障导航.在 Simulink 中建立轮椅运动学模型和创建模糊控制理论的模糊控制器,进行智能轮椅避障导航仿真.仿真结果表明,智能轮椅能有效完成室内避障,到达目的地,获得良好的避障导航效果.将该方案应用到智能轮椅上,将提高轮椅的智能水平,扩大其应用空间.     

基于多传感器融合的智能电动轮椅模糊测距控制

传统电动轮椅在复杂的外界环境及技术误差下,避障方法存在着误判率高,检测精准度低的问题。为了提高智能轮椅自动避障的安全性,设计基于多传感器融合技术,对智能轮椅实现模糊测距控制的智能控制器。能够根据电动轮椅配置的传感器数量和类型,可靠获取障碍物与轮椅之间的数据信息,并利用多传感器信息融合技术,分析预测障碍物相关的具体信息数据。在给定值的基础上,计算需要的多种控制变量,并进行模糊量化处理。根据模糊控制规则,在智能轮椅与障碍物模糊语言描述之间的关系下进行模糊决策,非模糊化处理,确保智能轮椅运行更加安全、稳定。     

残疾人轮椅智能避障功能创新研究

为研究电动轮椅的智能避障功能,该研究特点在于将HC-SR04超声波传感器和ZY101红外避障传感器相结合使轮椅对环境的感知更加准确,通过多传感器融合技术和模糊控制技术的研究进一步提高避障功能计算的精确度,使电动轮椅在实际行驶中可以自主地完成路线规划并躲避障碍物,更安全便捷地抵达目的地.     

基于计算机视觉的轮椅跟随系统设计

为解决老年人口日益增多而看护人员缺乏的问题,设计了一种具有自动跟随功能的智能轮椅系统。该系统通过计算机视觉传感器获取图像信息后,首先利用自适应高斯混合建模的背景减除法完成对目标的检测,再利用基于多特征融合的粒子滤波的TLD（Tracking-Learning-Detection）跟踪算法完成对目标的跟踪,最后结合双目定位算法得到目标在相机坐标系下的三维位置。根据目标的位置控制轮椅的速度和方向,使轮椅与目标人物保持设定的距离和相对方位,完成对目标的跟随。对轮椅跟随系统各项功能进行测试,结果表明,该系统不仅能够完成对使用者的实时跟随,同时也能实现对障碍物安全的躲避。     

基于双目视觉移动机器人的路径规划和避障研究

提出了一种移动机器人路径规划和避障的系统设计方案,实现了移动机器人自主行进的路径规划和自动避障功能.详细说明了如何采用立体视觉实现对环境的探测,利用图像处理算法的组合分离出地面、背景、障碍物和目标物,采用边界不变矩实现障碍物和目标物的区分,改进了经典的人工势场法进行路径的规划,根据模糊控制原理设计了避障控制器和避障规则.实际的运行结果表明了该系统的可行性和有效性,该系统实现了移动机器人利用自身传感器感知环境信息,动态规划行进路径,成功躲避障碍物等功能.     

复杂环境下的自由空间中自主跟随移动目标的多信息融合方法与应用

针对跟随机器人在多障碍物的自由空间中,难以对移动目标定位、运动估计并主动跟随的问题,提出一种复杂环境下的自由空间中自主跟随移动目标的多信息融合方法,在移动目标与跟随机器人之间建立多信号源冗余信道,通过扩散式信道切换观测多个信号源信息,合理设计权值进行信息融合,计算出移动目标的中心位置及运动速度和方向。由此,建立多信号源定位模型,分析得出跟随机器人与移动目标间出现障碍物时的跟随方法。在此基础上,设计了随动式的跟随定位系统并进行实验,结果表明:该方法能快速、准确地实现自由空间中跟随机器人在对移动目标的自主跟随。     

基于立体相机和UWB融合的移动机器人跟随方法

文中研究了人机共融环境下的自主跟随机器人。特别地,针对机器人确定所需跟随目标以及目标丢失后的重识别,提出了一种稳定有效的方法,即先基于立体相机的图像和点云数据实现对行人的视觉跟踪与定位;然后引入超宽带(Ultra Wide Band, UWB)的定位信息确定目标行人,并利用滤波算法融合传感器的数据得到相机坐标系下的坐标信息,最后利用坐标变换转为机器人坐标系下的位置。又提出了改进的动态窗口算法(Modified Dynamic Window Algorithm, MDWA),并将其作为机器人的跟随控制方法。另外,为保证机器人跟随能够持续稳定进行,基于传感器数据,提出了包含跟随行为、恢复行为、过渡行为的行为决策模块,通过行为间的切换,使机器人在面对因转弯抑或环境光照条件的变化使得相机失效而导致目标丢失时也能够重新找回目标。实验结果表明,所提出的跟随系统在开机时能够自动确定所需跟随目标,在有静态障碍物的场景,抑或是视野内有其他非目标行人干扰的动态场景下,机器人均能实现良好的避障跟随。特别地,机器人在转弯场景或是光照条件变化的场景下,机器人均可自主寻回被跟随目标,而且在转弯场景中,机器人的跟随...     

一种新颖的基于二分法和模糊控制的移动机器人避障系统

针对超声波传感器波束角窄导致移动机器人存在避障盲区的现状,研究了一种新颖的超声波避障系统。该系统采用六个超声波传感器构成特别设计的超声波阵列,实现无盲区检测中大型移动机器人前方及左右两侧障碍物的位置,充分保障运行安全性;同时在避障算法上,采用二分法和模糊控制相结合的控制算法,简化了模糊控制规则使系统具有很好的智能性和实时性,实现了移动机器人选择最佳避障路径并对新增的动态障碍物进行避障。将此避障控制系统应用于移动机器人上,实验结果表明：在未知环境下,实现对移动机器人周边的无盲区检测,并且能够实时根据周围障碍物的动态情况选择最佳避障路径,避免了其它避障控制算法中易出现的误避障和二次避障的情况。     

基于T-S模糊神经网络的智能轮椅避障控制策略

针对传统智能轮椅避障策略的路径规划效率差、功耗高等缺点,提出一种基于模糊神经网络的环境深度分区控制策略;利用红外、超声波和激光传感器的测量信息将待识别环境分为3个不同的深度区间,同时,利用T-S模糊神经网路算法融合异质传感器的测量信息,然后设计模糊控制规则,实现智能轮椅避障动作;最后建立智能轮椅的运动学模型和测量模型,并进行Simulink仿真测试;经仿真可知,该方法控制可靠,可快速无碰撞地通过障碍区,并能减少功耗,提高续航能力。     

Semi-autonomous Navigation of a Robotic Wheelchair

The present work considers the development of a wheelchair for people with special needs, which is capable of navigating semi-autonomously within its workspace. This system is expected to prove useful to people with impaired mobility and limited fine motor control of the upper extremities. Among the implemented behaviors of this robotic system are the avoidance of obstacles, the motion in the middle of the free space and the following of a moving target specified by the user (e.g., a person walking in front of the wheelchair). The wheelchair is equipped with sonars, which are used for distance measurement in preselected critical directions, and with a panoramic camera with a 360 degree field of view, which is used for following a moving target. After suitably processing the color sequence of the panoramic images using the color histogram of the desired target, the orientation of the target with respect to the wheelchair is determined, while its distance is determined by the sonars. The motion control laws developed for the system use the sensory data and take into account the non-holonomic kinematic constraints of the wheelchair, in order to guarantee certain desired features of the closed-loop system, such as stability. Moreover, they are as simplified as possible to minimize implementation requirements. An experimental prototype has been developed at ICS–FORTH, based on a commercially-available wheelchair. The sensors, the computing power and the electronics needed for the implementation of the navigation behaviors and of the user interfaces (touch screen, voice commands) were developed as add-on modules and integrated with the wheelchair.     

Simulation of Fuzzy-Logic-Based Intelligent Wheelchair Control System

Fuzzy logic control system for an intelligent wheelchair aimed for assistance by the severely handicapped persons is presented in the paper. It is based on a computer simulation of wheelchair navigation, in which fuzzy logic enables control priority to smoothly alternate between manual and automatic control of the wheelchair in the vicinity of obstacles. The main purpose of designing and simulating this control approach is to improve the safety of a wheelchair in the presence of obstacles. To analyze the success of the wheelchair control, a dynamic model of the wheelchair, together with the models of distance sensors, has been developed using Lagrange analysis.     

One-hand drive-type power-assisted wheelchair with a direction control device using pneumatic pressure

In this paper, we propose and develop a one-hand drive-type power-assisted wheelchair with a direction control device using pneumatic pressure sensors, for disabled persons who can use only their right or left arm. Compared with a joystick-type wheelchair, the advantages of the proposed wheelchair are that a disabled person can keep the functions of their arm, and can feel a sense that they are driving the wheelchair by the power of their arm. In the case of the wheelchair for disabled persons who can use only their right arm, the right wheel is rotated by the right hand and arm of the person. The left wheel is driven by an electric motor. For traveling in a straight line, the computer controls the motor as the angles of the right and left wheel are the same. When changing the direction of travel, the user uses a direction control device that consists of two vinyl tubes attached to both sides of a hand rim and pneumatic pressure sensors. Traveling experiments on a flat course with obstacles showed the validity of the proposed wheelchair system.     

基于AdaBoost算法的智能轮椅避障研究

随着计算机图像处理能力和技术的发展,视觉传感器在移动机器人导航和障碍物识别中的应用越来越受到重视.将AdaBoost算法用于智能轮椅的障碍物识别,在Visual C++6.0平台下,用AdaBoost算法训练得到用于障碍物检测的强分类器,然后利用该分类器进行检测出目标障碍物,并用模糊神经网络的方法对轮椅的声纳信息,视觉...     

未知环境中移动机器人实时导航与避障的分层模糊控制

为了解决单模糊控制器的“规则库爆炸”问题,设计了一种分层的模糊控制器,用于指导移动机器人通过未知环境到达指定的目标点．控制器根据8个超声传感器的信息和目标相对于机器人的方位确定机器人的运动．首先,每个超声传感器的信息被输入到危险度模糊控制器（DFC）中,产生关于周围环境中障碍物危险度的模糊向量．这些模糊向量经过融合与归一化处理后分别输入到上层的速度模糊控制器（VFC）和角速度模糊控制器（RFC）的推理机中．VFC根据目标的距离和障碍物的危险度控制机器人的前进速度．RFC根据目标的方向和障碍物的危险度控制机器人的转向,并采用最大隶属度法的反模糊化策略解决“对称不确定”问题．仿真与实验结果证明了所设计的模糊控制器简单而有效．     

在未知环境中基于模糊逻辑的移动机器人行为控制

本文介绍了一种在未知环境中基于模糊逻辑的移动机器人行为控制方法．传统的行为控制方法存在两个弱点：①行为不易描述；②多个行为之间的冲突和竞争难以协调．这篇文章的主要思想是将模糊逻辑控制与行为控制相结合致使这两个问题得到有效的解决．仿真实验结果表明：所提的方法通过多个行为如避障边沿行走和目标导向的融合，能够有效地对机器人在复杂和未知环境中导航．另外，该方法还适用于多传感器的融合与集成．     

A distributed fuzzy logic controller for an autonomous vehicle

Autonomous vehicles can be used in a variety of applications such as hazardous environments or intelligent highway systems. Fuzzy logic is an appropriate choice for this application as it can describe human behavior well. This paper proposes two fuzzy logic controllers for the steering and the velocity control of an autonomous vehicle. The two controllers are divided into separate modules to mimic the way humans think while driving. The steering controller is divided into four modules; one module drives the vehicle toward the target while another module avoids collision with obstacles. A third module drives the vehicle through mazes. The fourth module adjusts the final orientation of the target. The velocity controller is divided into three modules; the first module speeds up the vehicle to reach the target and slows it down as it moves toward the target. The second module controls the velocity in the neighborhood of obstacles. A third module controls the velocity of the vehicle as it turns sharp corners. A method for automatic tuning of the first module of the velocity controller is proposed to stabilize the velocity of the vehicle as it approaches the target. Two examples to demonstrate the interaction among the seven control modules are included. Results of the simulation are compared with those in the literature. © 2004 Wiley Periodicals, Inc.     

A microcomputer training system for electric wheelchair users

The problem addressed by this paper is the need to assess a severely physically handicapped person's ability to drive a joystick controlled electric wheelchair, and the parallel need for training in the use of a motorised chair. The only alternative assessment method is to obtain a motorised chair and place the person being assessed in it. This can involve considerable wasted expense if a chair is bought which subsequently proves to be unsuitable. When an unskilled person is practising using a motorised wheelchair constant supervision is necessary, which can be very time consuming.This paper outlines the development of a computer-based means of assessment and training for motorised wheelchair users. A suite of programs has been developed to run on a BBC microcomputer, which allows the ability of a severely physically handicapped person to be tested. The assessments which can be made include tests of the ability to make simple joystick movements in response to a prompt, and more complex investigations of the skills necessary to guide a wheelchair around barriers and obstacles. In addition to their use for assessment the programs can be used repeatedly for training, and a point-scoring system is included to indicate what improvement has been made.The software has been developed to resemble a computer game to facilitate its use with children, and makes extensive use of the BBC computer's colour graphics and sound generator. The software has been used by a number of establishments and individuals, and some user reactions are included in the paper.     

Advanced and Intelligent Control Techniques Applied to the Drive Control and Path Tracking Systems on a Robotic Wheelchair

This paper presents the theoretical support and experimental results of the application of advanced and intelligent control techniques to the drive control and trajectory tracking systems on a robotic wheelchair. The adaptive optimal control of the differential drive helps to improve the automatic guidance system's safety and comfort taking into consideration operating conditions such as load and distribution changes or motion actuator limitations. Furthermore, the incorporation of an optimal controller to minimize location errors and a fuzzy controller to adapt the linear velocity to the characteristics of the trajectory, provide the vehicle with a high degree of intelligence and autonomy, even when faced with obstacles. The global control solution implemented increases the features of the wheelchair for handicapped people, especially for those with a high degree of disability.