Feature-Based Proposal Density Optimization for Nonlinear Model Predictive Path Integral Control
- This paper presents a novel feature-based sampling strategy for nonlinear Model Predictive Path Integral (MPPI) control. In MPPI control, the optimal control is calculated by solving a stochastic optimal control problem online using the weighted inference of stochastic trajectories. While the algorithm can be excellently parallelized the closed- loop performance is dependent on the information quality of the drawn samples. Because these samples are drawn using a proposal density, its quality is crucial for the solver and thus the controller performance. In classical MPPI control, the explored state-space is strongly constrained by assumptions that refer to the control value variance, which are necessary for transforming the Hamilton-Jacobi-Bellman (HJB) equation into a linear second-order partial differential equation. To achieve excellent performance even with discontinuous cost-functions, in this novel approach, knowledge-based features are used to determine the proposal density and thus, the region of state- space for exploration. This paper addresses the question of how the performance of the MPPI algorithm can be improved using a feature-based mixture of base densities. Further, the developed algorithm is applied on an autonomous vessel that follows a track and concurrently avoids collisions using an emergency braking feature.
Author: | Hannes HomburgerORCiD, Stefan WirtensohnORCiD, Moritz DiehlORCiD, Johannes ReuterORCiD |
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DOI: | https://doi.org/10.1109/CCTA49430.2022.9966153 |
ISBN: | 978-1-6654-7338-5 |
ISBN: | 978-1-6654-7339-2 |
Parent Title (English): | Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA 2022), August 23-25, Trieste, Italy |
Publisher: | IEEE |
Document Type: | Conference Proceeding |
Language: | English |
Year of Publication: | 2022 |
Release Date: | 2022/11/10 |
Tag: | Predictive control; Nonlinear systems; Ships and offshore vessels |
First Page: | 1141 |
Last Page: | 1146 |
Institutes: | Institut für Systemdynamik - ISD |
Relevance: | Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband) |
Open Access?: | Nein |
Licence (German): | Urheberrechtlich geschützt |