This paper presents a new multi-layered algorithm for motion planning under motion and sensing uncertainties for Linear Temporal Logic specifications. We propose a technique to guide a sampling-based search tree in the combined task and belief space using trajectories from a simplified model of the system, to make the problem computationally tractable. Our method eliminates the need to construct fine and accurate finite abstractions. We prove correctness and probabilistic completeness of our algorithm, and illustrate the benefits of our approach on several case studies. Our results show that guidance with a simplified belief space model allows for significant speed-up in planning for complex specifications.

翻译：本文介绍了一种新的多层次算法,用于根据线性时空逻辑的动态和感知不确定性进行运动规划。我们提出了一种技术,用系统简化模型的轨迹来指导以取样为基础的搜索树,将任务和信仰空间结合起来,使问题在计算上可以移动。我们的方法消除了构建精细和准确的有限抽象学的需要。我们证明我们的算法是正确和概率完整的,并说明了我们在若干案例研究中的做法的好处。我们的结果显示,使用简化的信仰空间模型的指南可以大大加快复杂规格规划的速度。