This research proposes an automatic strategy for planning a team of identical robots evolving in a known environment. The robots should satisfy a global task for the whole team, given in terms of a Linear Temporal Logic (LTL) formula over predefined regions of interest. A Robot Motion Petri Net (RMPN) system is used for modeling the evolution of the robotic team in the environment, bringing the advantage of a fixed topology versus the number of robots, with respect to methods based on synchronous automaton products. The algorithmic method iterates the selection of an accepted run that satisfies the specification and the search for RMPN sequences of reachable markings that can produce desired observations. A Büchi automaton witnesses the advancement towards formula fulfillment, and at the core of our methods are three Mixed Integer Linear Programming (MILP) formulations that yield firing sequences and markings of RMPN model. The cost functions of these formulations reduce the number of robot synchronizations and induce collision avoidance. Simulation examples support the computational feasibility of the proposed method.

中文翻译：

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基于LTL规范和Petri网模型的机器人团队路径规划

这项研究提出了一种自动策略，用于规划在已知环境中进化的相同机器人团队。机器人应该满足整个团队的全局任务，根据预先定义的感兴趣区域的线性时间逻辑 (LTL) 公式给出。机器人运动 Petri Net (RMPN) 系统用于模拟机器人团队在环境中的演变，相对于基于同步自动机产品的方法，具有固定拓扑与机器人数量的优势。该算法方法迭代选择满足规范的可接受运行，并搜索可产生所需观察结果的可达标记的 RMPN 序列。Büchi 自动机见证了配方实现的进步，我们方法的核心是三个混合整数线性规划 (MILP) 公式，这些公式生成 RMPN 模型的点火序列和标记。这些公式的成本函数减少了机器人同步的次数并避免碰撞。仿真实例支持所提出方法的计算可行性。