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群制御arXiv:2309.01149

多ロボットステーションにおける衝突回避経路計画とスケジューリングの反復手法

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

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自動車製造ステーションで複数ロボットが協調作業する際のサイクルタイム最小化のため、タスク割当と衝突回避経路・スケジュールを反復的に解く手法を提案。

著者: Domenico Spensieri, Johan S. Carlson, Fredrik Ekstedt, Robert Bohlin

分類: cs.RO, cs.SY, eess.SY

原文アブストラクト

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, \emph{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 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.

関連論文

PR本紙発行元 EmplifAI