# Planning with SiMBA: Motion Planning under Uncertainty for Temporal Goals using Simplified Belief Guides

arXiv: https://arxiv.org/abs/2210.10202 · HTML: https://mlsanity.com/paper/2210.10202/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Oct 2022.

## Built on by (most cited first, 2 of 2)

- [Conformal Temporal Logic Planning using Large Language Models](https://mlsanity.com/paper/2309.10092/) (2023)
- [Sampling-based Reactive Synthesis for Nondeterministic Hybrid Systems](https://mlsanity.com/paper/2304.06876/) (2023)

## Abstract (arXiv)

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.