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A graph-based path planning algorithm for the control of tower cranes

机译:基于图的塔式起重机控制路径规划算法

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This paper presents a new path planning procedure for transportation tasks of three degrees of freedom tower cranes assuming a known, regularly updated and quadratic obstacle map derived by imaging sensors. Key objectives are the identification of either short, energy-efficient or low exciting load sway paths and the capability to be combined with an anti-sway controller and its trajectory generation module. An exact cell decomposition is carried out for the workspace of the tower crane introducing cells in the shape of circle parts. The height of each cell is determined considering the payload dimensions to ensure collision free paths. Moreover, a graph is derived by assigning a node to each cell and connecting the neighbors with circle arcs in tangential direction and lines in radial direction. The path finding is carried out utilizing an extended version of the novel graph searching algorithm $L^{st}$. The extension follows from the fact that the height costs depend on the investigated path and thus need to be considered during the search. A simulation example of a realistic scenario is provided in order to discuss the generated paths.
机译:本文提出了一种新的路径规划程序,用于旨在通过成像传感器衍生的已知,定期更新和二次障碍地图的三个自由塔起重机的运输任务。关键目标是识别短,节能或低励磁负载摇摆摇路径以及与防摇摆控制器及其轨迹产生模块结合的能力。为塔式绞合细胞的形状为圆形部件的塔式起重机的工作空间进行精确的细胞分解。考虑到有效载荷尺寸确定每个单元的高度,以确保自由路径。此外,通过将节点分配给每个小区并在切向方向和径向中的线路中将邻居连接到圆弧和线路的邻居来导出图表。使用新颖的图形搜索算法的扩展版本进行路径查找 $ l ^ { ast} $ 。延伸遵循的事实是,高度成本取决于所调查的路径,因此需要在搜索期间考虑。提供了一种仿真场景的模拟示例,以便讨论生成的路径。

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