# Safe Mission Planning under Dynamical Uncertainties

arXiv: https://arxiv.org/abs/2003.02913 · HTML: https://mlsanity.com/paper/2003.02913/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [Risk-Constrained Interactive Safety under Behavior Uncertainty for Autonomous Driving](https://mlsanity.com/paper/2102.03053/) (2021)

## Abstract (arXiv)

This paper considers safe robot mission planning in uncertain dynamical environments. This problem arises in applications such as surveillance, emergency rescue, and autonomous driving. It is a challenging problem due to modeling and integrating dynamical uncertainties into a safe planning framework, and finding a solution in a computationally tractable way. In this work, we first develop a probabilistic model for dynamical uncertainties. Then, we provide a framework to generate a path that maximizes safety for complex missions by incorporating the uncertainty model. We also devise a Monte Carlo method to obtain a safe path efficiently. Finally, we evaluate the performance of our approach and compare it to potential alternatives in several case studies.