Details
| Original language | English |
|---|---|
| Pages | 811-817 |
| Number of pages | 7 |
| Publication status | Published - Jun 2019 |
| Event | 2019 European Control Conference (ECC) - Naples, Italy Duration: 25 Jun 2019 → 28 Jun 2019 |
Conference
| Conference | 2019 European Control Conference (ECC) |
|---|---|
| Country/Territory | Italy |
| City | Naples |
| Period | 25 Jun 2019 → 28 Jun 2019 |
Abstract
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.
ASJC Scopus subject areas
- Mathematics(all)
- Control and Optimization
- Physics and Astronomy(all)
- Instrumentation
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2019. 811-817 Paper presented at 2019 European Control Conference (ECC), Naples, Italy.
Research output: Contribution to conference › Paper › Research
}
TY - CONF
T1 - Collision avoidance for uncertain nonlinear systems with moving obstacles using robust Model Predictive Control
AU - Soloperto, Raffaele
AU - Köhler, Johannes
AU - Allgöwer, Frank
AU - Müller, Matthias A.
N1 - Funding information: This work was supported by the International Max Planck Research School for Intelligent Systems (IMPRS-IS), and by the German Research Foundation under Grant GRK 2198/1.
PY - 2019/6
Y1 - 2019/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85071559491&partnerID=8YFLogxK
U2 - 10.23919/ECC.2019.8796049
DO - 10.23919/ECC.2019.8796049
M3 - Paper
SP - 811
EP - 817
T2 - 2019 European Control Conference (ECC)
Y2 - 25 June 2019 through 28 June 2019
ER -