基于虚拟子目标点的移动机器入路径规划

传统的反应式路径规划算法有时会出现＂死锁现象＂,为此设计了一种基于虚拟子目标点的移动机器人路径规划算法。首先根据已知的环境信息生成一条连接初始点和目标点的全局路径,移动机器人在沿全局路径行走时通过传感器探测周围的实时环境信息并寻找障碍物的转弯处,然后在该障碍物的转弯处设置虚拟子目标点,根据虚拟子目标点构建局部路径,机器人沿着局部路径走到该子目标点并进入下一个路径规划循环。仿真结果验证了该算法的有效性。     

基于模糊控制器的未知环境下移动机器人导航

研究机器人导航控制优化难题时,为实现未知环境中移动机器人自主导航并解决反应式导航策略中存在的局部陷阱问题,提出一种局部路径规划与目标切换相结合的导航方法.首先分析了移动机器人动力学模型,应用模糊推理构建反应式模糊控制器实现局部路径规划,并提出一种改进的目标切换方式,以机器人与目标相对方向的变化作为陷阱区域判断条件,当检测到陷阱情况时,引入合理的虚拟子目标,面向运动,直到脱离陷阱状态并恢复实际目标.方法可有效驱动机器人在复杂未知环境下以合理的路径脱离陷阱区域到达目标.仿真结果验证了方法的可行性和有效性,为应用于实际系统提供了可靠依据.     

移动机器人智能寻线导航与策略控制

寻线导航是移动机器人寻航方式之一，为使机器人沿地面标志线自主运动，并能在适时高线执行任务后自动返航，提出一种具有学习功能的智能寻线导航与策略控制方法以及系统模型，并将其应用于自行开发研制的导医机器人中．基于调制光检测原理，通过状态评判网络对多传感器信忠进行融合，通过Q学习方法获得高线走失后的最优控制策略．实现了机器人在各种复杂未知环境下稳定、可靠地工作．实验结果表明，该方法可以有效地提高机器人的适应性和智能度．     

同心圆策略下机器人路径滚动规划遗传算法

该文提出了一种新颖的全局静态环境未知时基于同心圆策略的机器人路径滚动规划遗传算法.该算法在机器人视野域内产生若干个同心圆进行环境建模,然后基于遗传算法根据当前机器人视野域信息和目标点规划出一条临时的导航路径,机器人沿着该导航路径前进一步,再由遗传算法重新规划新的导航路径.机器人导航路径不断进行动态修改,使机器人沿着一条...     

物联网环境下的助盲寻物机器人动态路径规划

近年来,盲人及低视力患者日益增多,世界上针对盲人及低视力患者的科研开发日渐普遍,基于RFID助盲语音寻物机器人是为了解决盲人家居寻物不便而开发的一款嵌入式产品。系统以盲人生活空间作为参考,构建虚拟仿真地图,并在寻径过程中实时监测现实环境更新仿真地图,动态规划寻径算法。参考Dijkstra算法与A Star算法,构建栅格法实现局部最优路径规划;参考蚁群算法构建出路径存储修正算法,与环路修正算法一起对栅格法进行修正和补充,逐步实现对全局最优路径的规划。降低了存储空间和提高了寻径效率,减少物理实现所需要功耗与实践,准确而且高效为盲人规划出最优前进路径,并引导盲人到达寻物点。     

全局未知环境下多机器人运动蚂蚁导航算法

研究了全局未知静态复杂环境下多机器人运动的导航问题,提出了一种新颖的蚂蚁导航算法.该方法将全局目标点映射到机器人视野域边界附近作为局部导航子目标,再由两组蚂蚁相互协作完成机器人视野域内局部最优路径的搜索,在此基础上进行与其他机器人的碰撞预测与避碰规划.机器人每前进一步都重复上述过程.因此,机器人前进路径不断地动态修改,从而在每条局部优化路径引导下,使机器人沿一条全局优化的路径到达目标点.仿真实验结果表明,即使在障碍物非常复杂的地理环境下,算法也能沿一条全局优化路径导航,且能安全避碰,效果十分令人满意.     

智能药品配送机器人

基于SLAM导航和计算机视觉技术自主研发了一款药品配送机器人用于代替医护人员按时按需为患者配送药品.机器人以US-C5300为核心主控,采用Linux操作系统,底部搭载12V电机以及全向轮给予机器人驱动力,同时配合激光雷达、摄像头、光敏传感器、扬声器、智能药盒等硬件设备,实现机器人自主寻径导航、人脸识别患者身份、摔倒检...     

未知环境下基于约束点的移动机器人路径规划

针对未知环境中障碍物种类多样性和位置不确定性的特点,提出了基于约束点的路径规划方法。首先对机器人在未知环境中检测到的局部障碍物信息进行分类和几何特征属性描述,得其约束点信息,然后引入改进后的A*算法,将其搜索范围局限于约束点上,计算约束点的评价函数值后得到子目标点,机器人到达子目标点后,若陷入死区,则采取回溯路径策略,重新选择子目标点,否则根据该点所属的障碍物种类采取跨越或绕行避障策略,最后移动机器人在未知环境中顺利到达目标点。仿真研究说明本文提出的路径规划方法具有可行性和有效性。     

一种寻线机器人实时控制系统的研究

针对寻线机器人实时控制的要求,提出了一种基于嵌入式实时操作系统uC/OS-Ⅱ和有限状态机相结合的寻线机器人系统设计方案.本方案以Renesas公司的H8/3048F-ONE型单片机为硬件核心,使用uC/OS-Ⅱ内核进行任务的管理与调度,并采用有限状态机的系统分析和程序设计方法设计了逻辑控制任务.行驶首圈采用光电传感器导航,同时生成路径地图;次圈及其以后采用基于地图和光电传感器的信息融合导航方法.实验结果表明,系统生成地图与实际路径地图吻合性好,24米路径次圈行驶的时间均比首圈少2-4s.系统在实时性、稳定性、可移植性和可扩展性等方面,更能满足寻线机器人发展的需要.     

一种移动机器人的禁忌搜索自主导航算法

纯粹的反应式导航算法在复杂未知环境下易陷入局部极小,为此提出一种基于局部子目标和禁忌搜索的自主导航算法．以当前可视区域内障碍物的关键角点为搜索邻域,利用禁忌搜索算法执行优化操作生成当前子目标,进而采用反应式导航算法对其进行跟踪,最终通过子目标的动态切换引导机器人驶达目标位置．算法可有效克服局部极小,显著提高机器人在复杂环境下的自主性．理论分析和仿真实验验证了算法的可行性和有效性．     

A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation.

Most conventional motion planning algorithms that are based on the model of the environment cannot perform well when dealing with the navigation problem for real-world mobile robots where the environment is unknown and can change dynamically. In this paper, a layered goal-oriented motion planning strategy using fuzzy logic is developed for a mobile robot navigating in an unknown environment. The information about the global goal and the long-range sensory data are used by the first layer of the planner to produce an intermediate goal, referred to as the way-point, that gives a favorable direction in terms of seeking the goal within the detected area. The second layer of the planner takes this way-point as a subgoal and, using short-range sensory data, guides the robot to reach the subgoal while avoiding collisions. The resulting path, connecting an initial point to a goal position, is similar to the path produced by the visibility graph motion planning method, but in this approach there is no assumption about the environment. Due to its simplicity and capability for real-time implementation, fuzzy logic has been used for the proposed motion planning strategy. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness of the proposed fuzzy navigation system.     

一种混合结构的移动机器人导航控制策略

研究了未知环境下移动机器人实时的导航控制问题.采用分布式系统将反射式行为、反应式行为与慎思规划相结合，设计了移动机器人导航控制策略.根据激光雷达传感器信息设计了基于栅格的实时避障算法和解锁策略.通过慎思规划解决了复杂环境下的局部势能陷阱问题.通过自行研制的移动机器人IMR01的实验验证了导航策略的有效性.     

基于人机交互的移动服务机器人导航系统

针对目前全自主移动机器人尚难实现的问题,基于人机结合的思想研制了由操作者、人机交互平台和移动机器人组成的“人—机—环境”一体化移动机器人导航系统．介绍了该系统的结构组成,阐述了系统导航策略,详细分析了人机交互、人机协作、移动机器人位姿预测及基于扩展卡尔曼滤波的位姿校正方法．设计了导航系统界面,通过在室内真实环境下的导航实验,验证了该“人—机—环境”一体化移动机器人导航系统的有效性．     

A Smooth Path Tracking Algorithm for Wheeled Mobile Robots with Dynamic Constraints

In order to avoid wheel slippage or mechanical damage during the mobile robot navigation, it is necessary tosmoothly change driving velocity or direction of the mobile robot. This means that dynamic constraints of the mobile robotshould be considered in the design of path tracking algorithm. In the study, a path tracking problem is formulated asfollowing a virtual target vehicle which is assumed to move exactly along the path with specified velocity. The drivingvelocity control law is designed basing on bang-bang control considering the acceleration bounds of driving wheels. Thesteering control law is designed by combining the bang-bang control with an intermediate path called the landing curve whichguides the robot to smoothly land on the virtual target's tangential line. The curvature and convergence analyses providesufficient stability conditions for the proposed path tracking controller. A series of path tracking simulations and experimentsconducted for a two-wheel driven mobile robot show the validity of the proposed algorithm.     

基于行为优先与模糊控制的移动机器人导航

由于动态未知环境下自主移动机器人的导航具有较大困难,为实现自主机器人在动态未知环境下的无碰撞运行,文中将行为优先级控制与模糊逻辑控制相结合,提出4种基本行为控制策略:目标寻找、避障、跟踪和解锁.针对'U'型和'V'型障碍物运行解锁问题,提出了行走路径记忆方法,并通过构建虚拟墙来避免机器人再次走入此类区域.仿真实验表明,所提出的控制策略可有效地运用于复杂和未知环境下自主移动机器人的导航,且具有较好的鲁棒性和适应性.     

An immunological approach to mobile robot reactive navigation

In this paper, a reactive immune network (RIN) is proposed and employed for mobile robot navigation within unknown environments. Rather than building a detailed mathematical model of artificial immune systems, this study tries to explore the principle in an immune network focusing on its self-organization, adaptive learning capability, and immune feedback. In addition, an adaptive virtual target method is integrated to solve the local minima problem in navigation. Several trapping situations designed by the early researchers are adopted to evaluate the performance of the proposed architecture. Simulation results show that the mobile robot is capable of avoiding obstacles, escaping traps, and reaching the goal efficiently and effectively.     

Wheeled mobile robot navigation using proportional navigation

We present a method for wheeled mobile robot navigation based on the proportional navigation law. This method integrates the robot's kinematics equations and geometric rules. According to the control strategy, the robot's angular velocity is proportional to the rate of turn of the angle of the line of sight that joins the robot and the goal. We derive a relative kinematics system which models the navigation problem of the robot in polar coordinates. The kinematics model captures the robot path as a function of the control law parameters. It turns out that different paths are obtained for different control parameters. Since the control parameters are real, the number of possible paths is infinite. Results concerning the navigation using our control law are rigorously proven. An extensive simulation confirms our theoretical results.     

A New Mobile Robot Toolbox for Matlab

In this study, a wheeled mobile robot navigation toolbox for Matlab is presented. The toolbox includes algorithms for 3D map design, static and dynamic path planning, point stabilization, localization, gap detection and collision avoidance. One can use the toolbox as a test platform for developing custom mobile robot navigation algorithms. The toolbox allows users to insert/remove obstacles to/from the robot’s workspace, upload/save a customized map and configure simulation parameters such as robot size, virtual sensor position, Kalman filter parameters for localization, speed controller and collision avoidance settings. It is possible to simulate data from a virtual laser imaging detection and ranging (LIDAR) sensor providing a map of the mobile robot’s immediate surroundings. Differential drive forward kinematic equations and extended Kalman filter (EKF) based localization scheme is used to determine where the robot will be located at each simulation step. The LIDAR data and the navigation process are visualized on the developed virtual reality interface. During the navigation of the robot, gap detection, dynamic path planning, collision avoidance and point stabilization procedures are implemented. Simulation results prove the efficacy of the algorithms implemented in the toolbox.     

环境特征提取在移动机器人导航中的应用

针对移动机器人在未知结构化环境中导航的需要,采用2D激光雷达作为主要传感器,对诸如墙壁、拐角、出口等这些典型的环境特征分别设计了一套有效的特征提取算法,并在该算法的基础上提出了基于特征点的移动机器人导航策略.该策略不需要里程计等其他一些内部传感器的信息,并且也不依赖具体的环境表述模型,从激光雷达扫描一次所得的数据中即可提取出环境特征,从而来指引机器人导航,实现起来快速可靠.应用到移动机器人MORCS-1上进行实验,取得了满意的结果,算法的实时性与鲁棒性得到了验证.