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.
@article{arxiv.2003.02913,
title = {Safe Mission Planning under Dynamical Uncertainties},
author = {Yimeng Lu and Maryam Kamgarpour},
journal= {arXiv preprint arXiv:2003.02913},
year = {2020}
}