@inproceedings{02e176e07acc4ecdb4a66a7fd92372d8,
title = "Risk-bounded Control using Stochastic Barrier Functions",
abstract = "In this paper, we design real-time controllers that react to uncertainties with stochastic characteristics and bound the probability of a failure in finite-time to a given desired value. Stochastic control barrier functions are used to derive sufficient conditions on the control input that bound the probability that the states of the system enter an unsafe region within a finite time. These conditions are combined with reachability conditions and used in an optimization problem to find the required control actions that lead the system to a goal set. We illustrate our theoretical development using a simulation of a lane-changing scenario in a highway with dense traffic.",
keywords = "Barrier Function, Robotics, Uncertainty",
author = "Shakiba Yaghoubi and Keyvan Majd and Georgios Fainekos and Tomoya Yamaguchi and Danil Prokhorov and Bardh Hoxha",
note = "Funding Information: S. Yaghoubi, T. Yamaguchi, D. Prokhorov, and B. Hoxha (<first name.last name>@toyota.com) are with the Toyota Research Institute of North America, Ann Arbor, MI, USA. K. Majd and G. Fainekos ({majd,fainekos}@asu.edu) are with CIDSE, Arizona State University, Tempe, AZ, USA. This research was partially funded by NSF OIA 1936997 Publisher Copyright: {\textcopyright} 2021 American Automatic Control Council.; 2021 American Control Conference, ACC 2021 ; Conference date: 25-05-2021 Through 28-05-2021",
year = "2021",
month = may,
day = "25",
doi = "10.23919/ACC50511.2021.9483118",
language = "English (US)",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1131--1136",
booktitle = "2021 American Control Conference, ACC 2021",
}