In this paper, we introduce an automata-based framework for planning with relaxed specifications. User relaxation preferences are represented as weighted finite state edit systems that capture permissible operations on the specification, substitution and deletion of tasks, with complex constraints on ordering and grouping. We propose a three-way product automaton construction method that allows us to compute minimal relaxation policies for the robots using standard shortest path algorithms. The three-way automaton captures the robot's motion, specification satisfaction, and available relaxations at the same time. Additionally, we consider a bi-objective problem that balances temporal relaxation of deadlines within specifications with changing and deleting tasks. Finally, we present the runtime performance and a case study that highlights different modalities of our framework.

中文翻译：

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具有宽松规范的基于自动机的优化规划

在本文中，我们介绍了一个基于自动机的框架，用于具有宽松规范的规划。用户松弛偏好表示为加权有限状态编辑系统，该系统捕获对任务的规范、替换和删除的许可操作，对排序和分组具有复杂的约束。我们提出了一种三向乘积自动机构造方法，该方法允许我们使用标准最短路径算法为机器人计算最小松弛策略。三路自动机同时捕获机器人的运动、规范满意度和可用的松弛。此外，我们考虑了一个双目标问题，该问题平衡了规范内截止日期的时间放松与更改和删除任务。最后，