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REAL-TIME PATH PLANNING IN UNKNOWN ENVIRONMENTS USING A VIRTUAL HILL

机译:使用虚拟山丘在未知环境中进行实时路径规划

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The artificial potential field based path planning has been most wisely used for local path planning because it provides simple and efficient motion planners for practical purposes. However, this approach has a local minimum problem which can trap a robot before reaching its goal. The local minimum problem is sometimes inevitable when a mobile robot moves in unknown environments, because the robot cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planning. In this study, we propose a new concept using a virtual hill to escape local minima that occur in local path planning for a mobile robot. A virtual hill is located around local minimum to repel a robot from local minimum.
机译:基于人工势场的路径规划最明智地用于本地路径规划,因为它为实际目的提供了简单有效的运动规划器。但是,这种方法存在局部最小问题,可以在达到目标之前将其困住。当移动机器人在未知环境中移动时,局部最小问题有时是不可避免的,因为机器人无法在检测到形成局部最小值的障碍之前预测局部最小值。在基于潜在领域的路径规划中,避免局部最小值一直是活跃的研究主题。在这项研究中,我们提出了一个新的概念,即使用虚拟丘陵避开在移动机器人的局部路径规划中出现的局部最小值。虚拟山丘位于局部最小值附近,以使机器人脱离局部最小值。

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