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2021 | OriginalPaper | Buchkapitel

Collision-Free Path Following of an Autonomous Vehicle Using NMPC

verfasst von : Ngo-Quoc-Huy Tran, Ionela Prodan, Nguyen-Duy-Minh Phan

Erschienen in: Advances in Engineering Research and Application

Verlag: Springer International Publishing

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Abstract

This paper deals with the obstacle avoidance problem for an autonomous vehicle using NMPC (Nonlinear Model Predictive Control) while following an a priori given path. The repulsive potential of the operating space is constructed from the bounded convex regions describing the static obstacles for collision-free navigation. The contribution lies in using the Hausdorff distances among the obstacles and the agent in order to activate/inactivate the repulsive potential field. This potential field component is introduced in a NMPC framework to penalize collision. This proposal shows good results in simulations and comparisons with our previous work.

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Vorheriges Kapitel Choice of Selection Methods in Genetic Algorithms for Power System State Estimation

Nächstes Kapitel Compare the Efficiency of the Active Filter and Active Rectifier to Reduce Harmonics and Compensate the Reactive Power in Frequency Controlled Electric Drive Systems

I.e., the computational complexity increases exponentially with the number of binary variables used in the problem formulation.

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I.e., our previous work which uses Chebyshev center instead of Hausdorff distance.

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The prediction horizon is chosen enough large to guarantee obstacle avoidance but not too large because of the computational burden of the solver.

It’s worth noting that the ship is very close the fixed obstacle 1 but does not collide due to the repulsive field.

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Titel: Collision-Free Path Following of an Autonomous Vehicle Using NMPC
verfasst von: Ngo-Quoc-Huy Tran
Ionela Prodan
Nguyen-Duy-Minh Phan
Verlag: Springer International Publishing
Buch: Advances in Engineering Research and Application
Print ISBN: 978-3-030-64718-6

Electronic ISBN: 978-3-030-64719-3

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-64719-3_27

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