A Caltech Library Service

A Scalable Controlled Set Invariance Framework with Practical Safety Guarantees

Gurriet, Thomas and Mote, Mark and Singletary, Andrew and Feron, Eric and Ames, Aaron D. (2019) A Scalable Controlled Set Invariance Framework with Practical Safety Guarantees. In: 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 2046-2053. ISBN 9781728113982.

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item:


Most existing methods for guaranteeing safety within robotics require time-consuming set-based computations, which greatly limit their applicability to real-world systems. In recent work, the authors have proposed a novel controlled set invariance framework to tackle this limitation. The framework uses a classical barrier function formulation, but replaces the difficult task of computing large control invariant sets with the more tractable tasks of (i) finding a controller that stabilizes the system to a backup set, and (ii) verifying that this backup set is invariant under the stabilizing controller. In this paper, we build upon these results to show that the requirement of proving invariance of the backup set can be relaxed at the expense of providing weaker guarantees on the safety of the system. This trade-off is shown to be favorable in practice, as the theoretically weaker safety guarantees are sufficient in many practical applications. The end result is a framework with a computational complexity that scales quadratically. The effectiveness of the approach is demonstrated in simulation on a Segway.

Item Type:Book Section
Related URLs:
URLURL TypeDescription
Gurriet, Thomas0000-0002-5240-3720
Singletary, Andrew0000-0001-6635-4256
Feron, Eric0000-0001-7717-2159
Ames, Aaron D.0000-0003-0848-3177
Additional Information:© 2019 IEEE. This work is supported by NSF award #1724457, #1446758 and #1555332. The authors would like to thank Claudia Kann for her valuable help in proofreading the present paper.
Funding AgencyGrant Number
Record Number:CaltechAUTHORS:20200917-151033700
Persistent URL:
Official Citation:T. Gurriet, M. Mote, A. Singletary, E. Feron and A. D. Ames, "A Scalable Controlled Set Invariance Framework with Practical Safety Guarantees," 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019, pp. 2046-2053, doi: 10.1109/CDC40024.2019.9030159
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105440
Deposited By: Tony Diaz
Deposited On:17 Sep 2020 23:34
Last Modified:16 Nov 2021 18:43

Repository Staff Only: item control page