激光雷达测距的机器人最优移动路径选择机制

针对当前机器人最优移动路径选择机制存在误差,工作效率低的缺陷,设计了基于激光雷达测距的机器人最优移动路径选择机制.首先利用人工势场方构建机器人的移动模型,并采用激光雷达测距技术建立栅格地图,然后将障碍物和机器人间的数据引入到坐标系中,经坐标转换映射到栅格地图中,建立障碍物与栅格地图之间联系;最后采用代价函数对机器人移动...     

基于双层蚁群算法和动态环境的机器人路径规划方法

针对动态环境未知时变的特点,提出一种机器人路径规划新方法.在该方法中,首先对栅格法建立的环境模型进行凸化处理,以避免机器人沿规划路径移动时陷入U型陷阱,从而加快路径规划的速度;其次,提出双层蚁群算法（DACO）,在每次迭代中先用外层蚁群算法寻找一条路径,然后以该路径为基础构造一个小环境,接着在该环境下用内层蚁群算法重新寻优,若寻得的路径质量更高,则更新路径并执行本文给出的一种新型信息素二次更新策略;最后,针对环境中不同动态障碍物的体积和速度,提出三种避障策略.动态环境下,机器人先由DACO算法规划一条静态环境下从起点到终点的全局最优路径,然后从当前起点开始,通过自带传感器获取动态环境信息,并根据需要执行等待、正碰或追尾避障策略,到达新的起点.仿真实验表明,该方法可以在动态环境下实时地为移动机器人规划出一条安全且最短的路径,是求解移动机器人路径规划问题的一种切实有效的方法.     

基于模糊算法的移动机器人路径规划

为了解决移动机器人最优路径规划问题,提出一种基于模糊算法的移动机器人路径规划策略.利用超声波传感器对环境进行探测,得到关于障碍物和目标的信息.运用模糊推理将障碍位置信息与目标位置信息模糊化,建立模糊规则并解模糊最终使机器人可以很好的避障,从而实现了移动机器人的路径规划.仿真实验结果表明了模糊算法优于势场法和A*算法,具...     

Safe Navigation of a Mobile Robot Considering Visibility of Environment

We present one approach to achieve safe navigation in an indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms possess fundamental limitations in that the robot can avoid only ldquovisiblerdquo ones among surrounded obstacles. In a real environment, it is not possible to detect all the dynamic obstacles around the robot. There are many occluded regions due to the limited field of view. In order to avoid collisions, it is desirable to exploit visibility information. This paper proposes a safe navigation scheme to reduce collision risk considering occluded dynamic obstacles. The robot's motion is controlled by the hybrid control scheme. The possibility of collision is dually reflected to path planning and speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The experimental results show that the robot moves along the safe path to obtain sufficient field of view. In addition, safe speed constraints are applied in motion control. It is experimentally verified that a robot safely navigates in dynamic indoor environment by adopting the proposed scheme.     

基于遗传算法和人工势场法的路径规划

在移动机器人的研究中,路劲规划是一个最基本也最复杂的问题。为了得到适合于机器人行走,以及全局最优的路径,采用遗传算法与人工势场法相结合的方法进行机器人的路径规划。首先采用遗传算法规划出全局最优或近似最优的无碰撞路径;再通过改进的人工势场法优化路径,增加路径节点,使路径更平滑。仿真实验结果表明,使用该方法所规划的路径是有效的和可行的。     

Teleoperation of a Mobile Robot Using a Force-Reflection Joystick With Sensing Mechanism of Rotating Magnetic Field

Operators’ intelligent and skillful decisions are necessary for the teleoperation of a mobile robot when there are many scattered obstacles. Among the sensors used for environment recognition, the camera is the most popular and powerful. However, there are several limitations in the camera-based teleoperation of a mobile robot. For example, shadowed and curved areas cannot be viewed using a narrow view-angle camera, especially in an environment with bad illumination and several obstacles. Therefore, it is necessary to have other sensory information for reliable teleoperations. In this study, 16 ultrasonic sensors are attached around a mobile robot in a ring pattern to measure the distances to the obstacles and a collision vector is introduced as a new tool for obstacle avoidance, which is defined as the normal vector from an obstacle to the mobile robot. Based on this collision vector, a virtual reflection force is generated to avoid the obstacles and then the reflection force is transferred to the operator who is holding the joystick used to control the mobile robot. Based on this reflection force, the operator can control the mobile robot more smoothly and safely. For this bidirectional teleoperation, a master joystick system using a two-axis hall sensor was designed to eliminate the nonlinear region, which exists in a general joystick with two motors and potentiometers. The effectiveness of the collision vector and force-reflection joystick is verified by comparing two vision-based teleoperation experiments, with and without force reflection.      

Instrumentation System for Blind Mobility Aid Simulation and Evaluation

A computer-linked instrumentation system for studies of blind mobility is described. The system uses mechanical position sensing, and is capable of monitoring the position of a moving subject to within approximately 2.5 cm over a large area (80 m2). This enables the computation of quantitative performance indices based on body trajectory through the environment. Head-mounted mobility aids with auditory displays can be simulated using the system. For this purpose head orientation is monitored, and environmental obstacle positions are stored. Computer-generated signals appropriate to the type of sensory aid under study and to the obstacles present are presented via head-phones to the mobile blind or blindfolded subject.     

Optimal motion planning and control of a nonholonomic spherical robot using dynamic programming approach: simulation and experimental results

Optimal motion planning and control of a nonholonomic spherical mobile robot is studied. Dynamic Programming (DP) as a direct and online approach is used to navigate the robot in an environment with/without obstacles. The optimal trajectory, which corresponds to the minimum cost, is determined in the case of presence of obstacles in the environment, and the robot can move towards the target optimally, without colliding with obstacles. DP yields optimal control inputs in a closed-loop form. In fact, a traditional control system is no longer needed to track the obtained trajectory since the resulted DP table includes optimal control inputs for every state in the admissible region. The effect of different final states and alternative intervals of the allowable state and control values are also studied. Results from several simulations show that the proposed method enables the robot to find an optimal trajectory from any given state towards a predefined target. An experimental setup is designed wherein a real spherical robot is driven according to the developed algorithm. A vision system monitors the robot and outputs the location/orientation of the robot at each step via image processing. Experimental results are then compared with simulations to validate the model and evaluate the control strategy.     

基于ARM平台的排障机器人控制系统设计

在吸收和改进其他移动机器人平台的基础上,提出了一种能在恶劣环境下排除障碍物的移动机器人方案。本排障机器人使用ARM处理器作为系统的中央处理单元,信息融合技术分别处理超声波传感器和CCD摄像机,将采集到的数据信息还原成作业信息。在实验室环境下能使其按照预定的路线运动,实现躲避障碍物的功能。     

煤矿井下基于Q—learning算法的移动机器人路径规划

机器人的路径规划一直是机器人研究领域的难点问题。针对煤矿井下环境的不确定性,环境的复杂使机器人很难得到好的规划结果。采用强化学习算法中的Q-learning算法实现井下移动机器人的局部路径规划,并对Q函数中的即时回报进行加权修正,使算法更有效地利用环境特征信息,进一步提高了避障能力。最后通过VC 进行仿真和模拟。仿真实验说明该方法的有效性和可行性。     

A path tracking control system for autonomous mobile robots: an experimental investigation

A path tracking control system developed for autonomous mobile robots driven by wheels is described. In conventional approaches, the path is usually planned by smooth curves with curvature-continuity and a path tracking controller is independently designed to compensate the path error occurring in the navigation. However, smooth path planning is difficult to execute on-line due to the computational burden. In addition, the conventional path tracking algorithm often causes unpredictable tracking motion when large path error occurs. In previous work, the present authors presented a bang-bang path tracking algorithm by which smooth and stable tracking motion could be obtained even for the path given by simple combination of straight lines or circles and its effectiveness was proven via preliminary simulation studies. However, there still remained the problem that the design parameter called landing coefficient could not be optimally chosen and performance verification through real system application was not accomplished. In this study, we improve the algorithm which can determine the design parameters analytically and verify its performance by implementing the algorithm in an actual mobile robot control system designed using a personal computer. To investigate the performance of the control system, a series of path tracking experiments was conducted for a two-wheel driven robot developed in the laboratory.     

The NavBelt-a computerized travel aid for the blind based on mobilerobotics technology

This paper presents a new concept for a travel aid for the blind. A prototype device, called the NavBelt, was developed to test this concept. The device can be used as a primary or secondary aid, and consists of a portable computer, ultrasonic sensors, and stereophonic headphone. The computer applies navigation and obstacle avoidance technologies that were developed originally for mobile robots. The computer then uses a stereophonic imaging technique to process the signals from the ultrasonic sensors and relays their information to the user via stereophonic headphones. The user can interpret the information as an acoustic “picture” of the surroundings, or, depending on the operational mode, as the recommended travel direction. The acoustic signals are transmitted as discrete beeps or continuous sounds. Experimental results with the NavBelt simulator and a portable prototype show that users can travel safely in an unfamiliar and cluttered environment at speeds of up to 0.8 m/s     

The Stanford Cart and the CMU Rover

The Stanford Cart was a remotely controlled TV-equipped mobile robot. A computer program was written which drove the Cart through cluttered spaces, gaining its knowledge of the world entirely from images broadcast by an on-board TV system. The CMU Rover is a more capable, and neatly operational, robot being built to develop and extend the Stanford work and to explore new directions. The Cart used several kinds of stereopsis to locate objects around it in three dimensions and to deduce its own motion. It planned an obstacle-avoiding path to a desired destination on the basis of a model built with this information. The plan changed as the Cart perceived new obstacles on its journey. The system was reliable for short runs, but slow. The Cart moved 1 m every 10 to 15 min, in lurches. After rolling a meter it stopped, took some pictures, and thought about them for a long time. Then it planned a new path, executed a little of it, and paused again. It successfully drove the Cart through several 20-m courses (each taking about 5 h) complex enough to necessitate three or four avoiding swerves; it failed in other trials in revealing ways. The Rover system has been designed with maximum mechanical and control system flexibility to support a wide range of research in perception and control. It features an omnidirectional steering system, a dozen on-board processors for essential real-time tasks, and a large remote computer to be helped by a high-speed digitizing/data playback unit and a high-performance array processor. Distributed high-level control software similar in organization to the Hearsay II speech-understanding system and the beginnings of a vision library are being readied. By analogy with the evolution of natural intelligence, we believe that incrementally solving the control and perception problems of an autonomous mobile mechanism is one of the best ways of arriving at general artificial intelligence.     

Rapid obstacle sensing using mobile robot sonar

This paper introduces rapid obstacle sensing using mobile robot sonar (ROSUM) a new method of applying simultaneous ultrasonic firing in environmental scanning. ROSUM focuses on treating undesirable crosstalk data with a heuristic pattern classification technique. In addition, least square curve fitting is applied to estimate bearing angles to the echoes’ reflecting points which partially eliminates the problem of sonar’s poor directionality. ROSUM enables full panorama scanning to be performed more rapidly then error eliminating rapid ultrasonic firing (EERUF), currently the most rapid method available. This makes ROSUM suitable for fast mobile robots navigating in dynamic environments since the system can detect obstacles which suddenly appear in the robot’s path, and which may not be detected by the low-frequency scans in time for the robot to safely avoid them. Criteria for sonar ring design enabling multi-wave superposition to attain a quasi-homogenous sonar beam intensity pattern are also outlined. ROSUM has been implemented and tested in a specular office-like environment using a mobile robot. As a result, obstacle detection was performed not only faster, but also more accurately in comparison to conventional methods.     

一种移动机器人的运动控制方法研究

针对反应式移动机器人运动控制中存在的缺乏自主运动规划等问题,介绍了一种新型移动机器人的运动控制方法。设计了一种混合式控制结构实现移动机器人的运动控制。采用基于行为的运动控制策略,将反应式行为和规划行为融合在一起。实验结果表明该策略能够很好地完成复杂环境下移动机器人的运动控制。     

基于混合蛙跳算法的移动机器人路径规划

针对移动机器人路径规划中算法搜索能力不强且易陷入停滞的问题,文中提出了一种基于混合蛙跳算法的移动机器人路径规划方法。首先利用蚁群算法在栅格地图中生成一定数量的路径,然后引入混合蛙跳算法,子群内进行Memetic进化,最坏青蛙根据与子群最优青蛙或全局最优青蛙的路径交点栅格进行路径更新,并对最终生成的最优路径进行优化处理,以消除不必要的拐点,保证机器人路径运行的安全性。二维环境下的仿真实验表明,提出的混合蛙跳算法能在有效避开障碍物的同时快速地规划出一条通往目标点的优化路径,且效果令人满意。     

基于红外的障碍场中集群微机器人的控制方法

对多障碍物环境下微机器人集群运动的控制问题进行了研究.结合微机器人尺寸小的特点,采用低功耗的红外传感器感知外界环境.设定机器人的安全区域,根据机器人运动过程中避障和路径规划所要满足的边界条件,提出了基于人工蜂群问题优化的路径规划控制模型,实现了微机器人的避障和路径规划.仿真结果验证了该控制方法的有效性.     

Optimal control at energy performance index of the mobile robots following dynamically created trajectories

In practice, the problem of motion control of the wheeled mobile robots is often neglected. Wheeled mobile robots are strongly nonlinear systems and restricted by non-holonomic constraints. Motion control of such systems is not trivial task and usage of non-optimal control signals can lead to deterioration of the overall robot system's performance. In case of autonomous application of the mobile robots all parts of its control system should work perfectly. The paper presents the theory and application of the optimal control method at the energy performance index towards motion control of the two-wheeled mobile robot during the realisation of complex, dynamically created trajectories. With the use of the proposed control method the two-wheeled mobile robot can realise effectively the desired trajectory, which is generated ad-hoc by the navigation system of the robot. Thus the proposed method can be used for motion control of autonomous or semi-autonomous wheeled mobile robots. The presented results of both computer simulations and experiments indicate that the proposed method works effectively from the point of view of the motion control of two-wheeled mobile robot. Movement of the mobile robot appeared reliable and predictable during all the tests.     

免疫算法在移动机器人路径规划中的应用

具体阐述了免疫算法在移动机器人路径规划中的应用,使机器人从给定点到目标点可以有效地躲避障碍物而且找到一条最短的路径;构建了机器人的数学模型和亲和力函数,并且说明了机器人的控制方式,给出了算法的具体实现步骤以及仿真实验。实验结果表明,免疫算法在应用到移动机器人路径规划时具有良好的性能。