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An Iterative Approach for Collision Free Routing and Scheduling in Multirobot Stations

机译:多机器人站无冲突路由与调度的迭代方法

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This work is inspired by the problem of planning sequences of operations, as welding, in car manufacturing stations where multiple industrial robots cooperate. The goal is to minimize the station cycle time, i.e., the time it takes for the last robot to finish its cycle. This is done by dispatching the tasks among the robots, and by routing and scheduling the robots in a collision-free way, such that they perform all predefined tasks. We propose an iterative and decoupled approach in order to cope with the high complexity of the problem. First, collisions among robots are neglected, leading to a min–max Multiple Generalized Traveling Salesman Problem (MGTSP). Then, when the sets of robot loads have been obtained and fixed, we sequence and schedule their tasks, with the aim to avoid conflicts. The first problem (min–max MGTSP) is solved by an exact branch and bound (B&B) method, where different lower bounds are presented by combining the solutions of a min–max set partitioning problem and of a Generalized Traveling Salesman Problem (GTSP). The second problem is approached by assuming that robots move synchronously: a novel transformation of this synchronous problem into a GTSP is presented. Eventually, in order to provide complete robot solutions, we include path planning functionalities, allowing the robots to avoid collisions with the static environment and among themselves. These steps are iterated until a satisfying solution is obtained. Experimental results are shown for both problems and for their combination. We even show the results of the iterative method, applied to an industrial test case adapted from a stud welding station in a car manufacturing line.
机译:这项工作的灵感来自于在多个工业机器人合作的汽车制造站中计划焊接操作顺序的问题。目的是最大程度地减少工作站的循环时间,即最后一个机器人完成循环所花费的时间。通过在机器人之间分配任务,以及以无冲突的方式路由和调度机器人,以使其执行所有预定义的任务,可以完成此任务。为了解决问题的高度复杂性,我们提出了一种迭代和解耦的方法。首先,忽略了机器人之间的碰撞,从而导致了最小-最大多重广义旅行商问题(MGTSP)。然后,当获取并固定了机器人负载集后,我们将对它们的任务进行排序和安排,以期避免冲突。第一个问题(最小-最大MGTSP)是通过精确的分支定界(B&B)方法解决的,其中结合了最小-最大集划分问题和广义旅行商问题(GTSP)的解决方案来给出不同的下界。通过假设机器人同步运动来解决第二个问题:提出了将该同步问题转换为GTSP的新方法。最终,为了提供完整的机器人解决方案,我们包括了路径规划功能,使机器人可以避免与静态环境以及彼此之间的碰撞。重复这些步骤,直到获得满意的解决方案。实验结果显示了这两个问题及其组合。我们甚至展示了迭代方法的结果,该方法应用于从汽车生产线中的螺柱焊接站改编的工业测试用例中。

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