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An obstacle avoidance method for mobile robots based on fuzzy decision-making

机译:基于模糊决策的移动机器人避障方法

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摘要

In this paper, an obstacle avoidance method for wheeled mobile robots is proposed, based on selection of the local target points of robot's movement called "via-points" which are defined in a navigation space, generated by taking into consideration a smooth robot motion. The proposed algorithm utilizes a fuzzy multi-attribute decision-making method in which three fuzzy goals are defined to achieve successful robot navigation by deciding the via-point the robot would proceed at each control step. Via-point is defined as the local target point of a robot's movement at each decision instance. Three fuzzy goals to achieve successful robot navigation are defined. At each decision step, a set of the candidates of a next via-point in a 2D navigation space is constructed by combining various heading angles and velocities. Given the fuzzy goals, the fuzzy decision making enables the robot to choose the best via-point among the candidates. An efficient scheme for local minimum recovery from trapped-in situation is also provided. A series of simulations has been performed to study the effects of associated navigation parameters on the navigation performances. The method has been implemented on an actual mobile robot and experimented in real environments. Results from a series of simulations and experiments conducted in real environments show the validity and effectiveness of the proposed navigation method.
机译:在本文中,提出了一种轮式移动机器人的避障方法,该方法基于对机器人运动的局部目标点(称为“通点”)的选择,该目标点是在导航空间中定义的,并考虑了机器人的平稳运动。所提出的算法利用模糊多属性决策方法,其中定义了三个模糊目标,以通过确定机器人在每个控制步骤进行的通孔来实现成功的机器人导航。通孔点定义为每个决策实例中机器人运动的本地目标点。定义了实现机器人成功导航的三个模糊目标。在每个决策步骤中,通过组合各种航向角和速度来构造2D导航空间中下一个过孔点的候选集。在给出模糊目标的情况下,模糊决策可使机器人在候选对象中选择最佳通孔。还提供了一种有效的方案,可以从陷入的情况中进行本地最小恢复。已经进行了一系列模拟以研究相关的导航参数对导航性能的影响。该方法已在实际的移动机器人上实现,并在实际环境中进行了实验。在真实环境中进行的一系列模拟和实验结果表明,该导航方法的有效性和有效性。

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