Collision avoidance for uncertain nonlinear systems with moving obstacles using robust Model Predictive Control

In this paper, we provide a novel robust collision avoidance approach that is based on a general tube-based MPC framework. We consider collision avoidance for general nonlinear uncertain systems with moving obstacles. The resulting optimization problem can be handled by standard nonlinear programmin...

Full description

Saved in:
Bibliographic Details
Published in2019 18th European Control Conference (ECC) pp. 811 - 817
Main Authors Soloperto, Raffaele, Kohler, Johannes, Allguwer, Frank, Muller, Matthias A.
Format Conference Proceeding
LanguageEnglish
Published EUCA 01.06.2019
Subjects
Automobiles
Collision avoidance
Europe
Nonlinear systems
Optimization
Predictive control
Programming
Uncertain systems
Online AccessGet full text
DOI10.23919/ECC.2019.8796049

Cover

More Information
Summary:In this paper, we provide a novel robust collision avoidance approach that is based on a general tube-based MPC framework. We consider collision avoidance for general nonlinear uncertain systems with moving obstacles. The resulting optimization problem can be handled by standard nonlinear programming solvers. Moreover, we provide formal guarantees, such as recursive feasibility, constraint satisfaction, as well as robust collision avoidance. We demonstrate the efficacy of the proposed method through a simulation of an autonomous car during realistic manoeuvres.
DOI:10.23919/ECC.2019.8796049