A model predictive control scheme for mobile robotic vehicles in dynamic environments

Author

Franze, Giuseppe ; Lucia, Walter

Author_Institution

DIMES, Univ. degli Studi della Calabria, Rende, Italy

fYear

2013

fDate

10-13 Dec. 2013

Firstpage

5752

Lastpage

5757

Abstract

This paper considers the obstacle avoidance motion planning problem for autonomous vehicles operating in uncertain dynamic environments. By resorting to a set-theoretic approach, a receding horizon control algorithm is developed for robots described by linear time-invariant (LTI) systems subject to disturbance effects, input and state constraints. The resulting scheme guarantees Uniformly Ultimate Boundedness and constraints fulfilment regardless of any obstacle configuration occurrence.

Keywords

collision avoidance; linear systems; mobile robots; predictive control; set theory; uncertain systems; LTI systems; autonomous vehicles; constraints fulfilment; disturbance effects; linear time-invariant systems; mobile robotic vehicles; model predictive control scheme; obstacle avoidance motion planning problem; obstacle configuration occurrence; receding horizon control algorithm; set-theoretic approach; uncertain dynamic environments; uniformly ultimate boundedness; Collision avoidance; Dynamics; Planning; Robots; Robustness; Trajectory; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on

Conference_Location

Firenze

ISSN

0743-1546

Print_ISBN

978-1-4673-5714-2

Type

conf

DOI

10.1109/CDC.2013.6760796

Filename

6760796