论文标题

SDSS-V算法:快速,无碰撞轨迹计划,重叠的机器人纤维定位​​器

SDSS-V Algorithms: Fast, Collision-Free Trajectory Planning for Heavily Overlapping Robotic Fiber Positioners

论文作者

Sayres, Conor, Sánchez-Gallego, José R., Blanton, Michael R., Araujo, Ricardo, Bouri, Mohamed, Grossen, Loïc, Kneib, Jean-Paul, Kollmeier, Juna A., Kronig, Luzius, Pogge, Richard W., Tuttle, Sarah

论文摘要

机器人纤维定位​​器(RFP)阵列在大量多重光谱调查工具中广泛采用。 RFP阵列通过田野和暴露之间的快速重新配置来减少夜间操作开销。与类似仪器相比,SDSS-V选择了一种非常致密的RFP填料方案,其中三个或多个机器人通常可以访问场中的任何点。该设计为目标分配提供了灵活性。但是,无碰撞轨迹计划的任务尤其具有挑战性。我们提出了两种多代理分布式控制策略,它们高效且在计算上很便宜,用于确定重叠的工作空间中RFP的无碰撞路径。我们证明,如果“折叠”状态(将所有机器人臂撤回并在类似晶格的方向上对齐),可以有效地找到两个任意机器人配置之间的重新配置路径,则可以在初始状态和最终状态之间插入。尽管为SDSS-V开发了开发,但我们描述的方法是通用的,因此适用于广泛的RFP设计和布局。机器人纤维定位​​器技术继续迅速发展,在不久的将来,超填充的RFP设计可能是可行的。我们的算法在非常拥挤的环境中特别有能力路由路径,即使在政权中,我们也比SDSS-V RFP设计更加拥挤。

Robotic fiber positioner (RFP) arrays are becoming heavily adopted in wide field massively multiplexed spectroscopic survey instruments. RFP arrays decrease nightly operational overheads through rapid reconfiguration between fields and exposures. In comparison to similar instruments, SDSS-V has selected a very dense RFP packing scheme where any point in a field is typically accessible to three or more robots. This design provides flexibility in target assignment. However, the task of collision-less trajectory planning is especially challenging. We present two multi-agent distributed control strategies that are highly efficient and computationally inexpensive for determining collision-free paths for RFPs in heavily overlapping workspaces. We demonstrate that a reconfiguration path between two arbitrary robot configurations can be efficiently found if "folded" state, in which all robot arms are retracted and aligned in a lattice-like orientation, is inserted between the initial and final states. Although developed for SDSS-V, the approach we describe is generic and so applicable to a wide range of RFP designs and layouts. Robotic fiber positioner technology continues to advance rapidly, and in the near future ultra-densely packed RFP designs may be feasible. Our algorithms are especially capable in routing paths in very crowded environments, where we see efficient results even in regimes significantly more crowded than the SDSS-V RFP design.

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