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Path Planning for Automatic Guided Vehicle with Multiple Target Points in Known Environment

机译:具有多个目标点的自动导向车辆在已知环境中的路径规划

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Today, Automatic Guided Vehicles (AGVs) with a path planning algorithm are being used in many industrial fields. There are A*, D*, and D* lite algorithms in the path planning algorithm. In this paper, propose a modified D* lite algorithm using the most efficient D* lite among these algorithms. The modified D* lite path planning algorithm is proposed to improve these D* lite path planning algorithm's weaknesses such as traversing across obstacles sharp corners, or traversing between two obstacles. The modified D* lite path planning algorithm has function to set target points differently from the existing D* lite path planning algorithm. To do this task, the followings are done. First, a work space is divided into square cells. Second, cost of each edge connecting current node to neighbor nodes is calculated. Third, the shortest paths from the initial point to all multiple target points are computed and the shortest paths from any target point to remaining target points including the goal point are computed by using Hamilton path. Fourth, a cost-minimal path is re-calculated as soon as the laser sensor detects an obstacle and make an updated list of target points. Finally, the validity of the proposed modified D* lite path planning algorithm is verified through simulation and experimental results in known environment.
机译:今天,自动导引车(AGV的)与路径规划算法被在许多工业领域。有A *,d *和d *精简版在路径规划算法的算法。在本文中,提出了一种改进d *精简版算法使用最高效的d *这些算法中精简版。修正后的d *精简版的路径规划算法,以改善这些d *精简版路径规划算法的弱点,如跨越障碍物穿越尖角,或两个障碍物之间穿越。修正后的d *精简版路径规划算法函数以不同的方式设定的目标点从现有d *精简版路径规划算法。为执行此任务,请执行以下操作。首先,工作空间分为方形电池。其次,计算每个边缘连接电流节点到邻居节点的成本。第三,计算来自初始点到所有多个目标点的最短路径,并且通过使用汉密尔顿路径计算来自任何目标点到包括目标点的剩余目标点的最短路径。第四,一旦激光传感器检测到障碍物并制作更新的目标点列表,就会重新计算成本最小路径。最后,建议修改d的有效性*精简版的路径规划算法,通过仿真和实验结果中已知的环境验证。

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