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An advanced potential field method proposed for mobile robot path planning

机译:用于移动机器人路径规划的高级潜在场方法

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In this paper, both the local minimum and the goal non-reachable with obstacles nearby (GNRON) problems have been solved on the artificial potential field (APF) for mobile robot path planning in a bounded environment. The GNRON problem occurs when the goal's position is inside the circle of influence of the obstacle. This phenomenon gives rise to a larger repulsive force with regard to the attractive force. Therefore, a stronger attractive function is proposed to ensure that the robot reaches the target successfully. The local minimum problem occurs when the robot, the goal and the centre of the obstacle are aligned. This situation engenders a total potential force equal to zero before reaching the goal position. To overcome this problem, a novel of repulsive potential function is proposed by activating a virtual escaping force when a local minimum is detected. This force behaves as a rotational force allowing the robot to escape from the deadlock positions and turn smoothly away from obstacles in the direction of the target. The combination of the new attractive force and the novel repulsive force could solve the local minimum and the GNRON problems. Finally, some methodic simulations, based on a comparative study with other methods from the literature, are carried out to validate and demonstrate the effectiveness of the advanced potential field method to handle the local minimum and GNRON problems.
机译:在本文中,在有界环境中的移动机器人路径规划的人工势域(APF)上已经解决了附近的局部最小值和局部的局部最小值和目标,用于移动机器人路径规划的障碍物。当目标的位置在障碍物的影响圈内时,会出现八龙问题。这种现象引起了对吸引力的更大的排斥力。因此,提出了更强大的有吸引力的功能,以确保机器人成功地达到目标。当机器人,目标和障碍物的中心对齐时,会发生局部最小问题。这种情况在到达目标位置之前,参加总势力等于零。为了克服这个问题,通过在检测到局部最小值时激活虚拟逸出力来提出一种新的排斥潜在功能。该力表现为旋转力,允许机器人从死锁位置逸出并在目标方向上平滑地远离障碍物。新的吸引力和新的排斥力的组合可以解决局部最小和泳池问题。最后,基于与来自文献的其他方法的比较研究的一些方法模拟,以验证并证明了先进的潜在现场方法处理局部最小值和金属问题的有效性。

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