This paper addresses the problem of temporal logic motion planning for an autonomous robot operating in an unknown environment. The objective is to enable the robot to satisfy a syntactically co-safe Linear Temporal Logic (scLTL) specification when the exact locations of the desired labels are not known a priori. We introduce a new type of automaton state, referred to as commit states. These states capture intermediate task progress resulting from actions whose consequences are irreversible. In other words, certain future paths to satisfaction become not feasible after taking those actions that lead to the commit states. By leveraging commit states, we propose a sound and complete frontier-based exploration algorithm that strategically guides the robot to make progress toward the task while preserving all possible ways of satisfying it. The efficacy of the proposed method is validated through simulations.

翻译：本文研究了自主机器人在未知环境中运行时面临的时序逻辑运动规划问题。目标是在期望标签的确切位置未知的情况下，使机器人能够满足语法安全的线性时序逻辑（scLTL）规范。我们引入了一种新型自动机状态，称为承诺状态。这些状态捕获了由不可逆动作所产生的中期任务进展。换言之，在执行那些导致承诺状态的动作后，某些满足规范的未来路径将不再可行。通过利用承诺状态，我们提出了一种完备且可靠的前沿探索算法，该算法能策略性地引导机器人在保持所有可能满足任务方式的同时推进任务进展。仿真实验验证了所提方法的有效性。