论文标题
与SIMBA进行计划：使用简化的信念指南的时间目标不确定性的运动计划
Planning with SiMBA: Motion Planning under Uncertainty for Temporal Goals using Simplified Belief Guides
论文作者
论文摘要
本文提出了一种新的多层算法，用于在运动下进行运动计划，并感知线性时间逻辑规范的不确定性。我们提出了一种技术，可以使用系统的简化模型中的轨迹在组合的任务和信念空间中指导基于采样的搜索树，以使问题计算可探讨。我们的方法消除了构建精细而准确的有限抽象的需求。我们证明了算法的正确性和概率完整性，并说明了我们方法对几个案例研究的好处。我们的结果表明，通过简化的信念空间模型的指导可以在规划复杂规范的规划中大大加速。
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.
