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基于超声波传感器的未知狭窄环境导航算法 总被引:2,自引:0,他引:2
针对移动机器人在未知狭窄环境中的导航问题,利用证据理论中的矛盾因子,给出了一个自适应超声波传感器模型。利用该模型,结合D S证据理论融合算法以及证据格方法,实现了移动机器人在未知狭窄环境中的导航,并有效地减少了由于超声波传感器镜面反射所引起的不确定性。实验结果表明了该方法的有效性。 相似文献
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针对变化和部分未知环境下的移动机器人导航,将示例学习和生命科学中的免疫原理、进化算法相结合,将过去进化过程中的经验(性能好的个体)通过示例表达,提出了一种结合示例学习的移动机器人免疫进化路径规划算法。该算法将示例中的路径片段通过进化机制与免疫操作等其他进化操作所产生的新路径片段相互高效地组合,能够快速地进化出全局(次)最优可行路径。借助仿真实验和一些理论分析,分析了示例学习如何有效地利用过去的经验来解决部分未知和变化环境下的路径规划问题,分析了所构造的免疫算子对算法的影响。 相似文献
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基于模糊控制器的未知环境下移动机器人导航 总被引:1,自引:0,他引:1
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. 相似文献
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在未知环境中基于模糊逻辑的移动机器人行为控制 总被引:3,自引:1,他引:2
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. 相似文献
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采用2D激光雷达作为主要传感器,设计了一种未知室内环境下的移动机器人导航策略;该策略首先把机器人室内环境下的导航行为分为3个状态集:墙壁导航、走廊导航和通路导航,然后利用有限状态自动机的原理把这几种状态集融合到一起,构成了一种移动机器人自主探索未知环境的导航策略;该策略的特点在于不依赖里程计的信息,并且也不需要任何的环境地图,实现起来快速准确,对于环境的变化具有较强的鲁棒性;将该策略应用到移动机器人MORCS-1上进行了测试,实验结果表明了算法具有良好的实时性与可靠性. 相似文献
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基于不确定网格地图的移动机器人导航 总被引:1,自引:0,他引:1
研究了在未知环境下的移动机器人导航问题.在分析超声传感器不确定性模型的基础上,根据模糊集理论创建网格地图来描述机器人工作环境,使用模糊隶属度表示网格占用状态.通过网格信息融合来减弱传感器测量误差,提高网格地图的精度.提出基于模糊网格地图的路径规划算法,利用重复局部优化路径搜索来实现全局路径规划.机器人通过交替进行创建地图和路径规划两个基本过程来完成导航任务.仿真结果表明创建的地图能较精确地表示环境信息。规划的路径可以使机器人安全地到达目的地. 相似文献
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基于多Agent的移动机器人导航进化控制的体系结构 总被引:4,自引:0,他引:4
将进化控制与多Agent技术相结合,兼顾几种经典体系结构的优点,提出了一种基于多Agent的移动机器人导航进化控制的体系结构.该体系结构特别适合于网络环境下的机器人系统,能充分发挥进化控制隐含并行性的优点.最后,结合其所在研究所实验室的条件,设计出以该体系结构为基础机器人系统实现方案. 相似文献
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This paper describes a mobile robot navigation control system based on fuzzy logic. Fuzzy rules embedded in the controller of a mobile robot enable it to avoid obstacles in a cluttered environment that includes other mobile robots. So that the robots do not collide against one another, each robot also incorporates a set of collision prevention rules implemented as a Petri Net model within its controller. The navigation control system has been tested in simulation and on actual mobile robots. The paper presents the results of the tests to demonstrate that the system enables multiple robots to roam freely searching for and successfully finding targets in an unknown environment containing obstacles without hitting the obstacles or one another. 相似文献
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In this paper, a new approach is developed for solving the problem of mobile robot path planning in an unknown dynamic environment based on Q-learning. Q-learning algorithms have been used widely for solving real world problems, especially in robotics since it has been proved to give reliable and efficient solutions due to its simple and well developed theory. However, most of the researchers who tried to use Q-learning for solving the mobile robot navigation problem dealt with static environments; they avoided using it for dynamic environments because it is a more complex problem that has infinite number of states. This great number of states makes the training for the intelligent agent very difficult. In this paper, the Q-learning algorithm was applied for solving the mobile robot navigation in dynamic environment problem by limiting the number of states based on a new definition for the states space. This has the effect of reducing the size of the Q-table and hence, increasing the speed of the navigation algorithm. The conducted experimental simulation scenarios indicate the strength of the new proposed approach for mobile robot navigation in dynamic environment. The results show that the new approach has a high Hit rate and that the robot succeeded to reach its target in a collision free path in most cases which is the most desirable feature in any navigation algorithm. 相似文献
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In this paper, a novel algorithm is developed to achieve efficient and smooth navigation for a differential drive mobile robot in unknown environments. The algorithm takes advantage of the essential characteristics of a differential drive robot and combines fuzzy logic with the ideas of Braitenberg vehicles. We have also proposed and tested a new technique for tuning a membership function referred to as NEAR, representing the closeness of the robot to an obstacle. The tuning scheme is obtained based on the distribution directives of the range sensors on the robot. The resulting navigation algorithm has been implemented on a real mobile robot and tested in various environments. Some problems in the implemented algorithm are identified and effective solutions are proposed. Experimental results are presented which demonstrate the effectiveness and improved performance of the resulting Fuzzy–Braitenberg navigation scheme.This research was supported in part by the National Sciences and Engineering Research Council (NSERC) of Canada under grants RGPIN1345 and RGPIN227612, and the Canada Foundation for Innovation under the New Opportunities Program. 相似文献
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Xiaoyu Yang Mehrdad Moallem Rajni V Patel 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2005,35(6):1214-1224
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. 相似文献
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环境特征提取在移动机器人导航中的应用 总被引:1,自引:0,他引:1
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. 相似文献