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Collision-Free Path Following of an Autonomous Vehicle Using NMPC

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Advances in Engineering Research and Application (ICERA 2020)

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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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Notes

  1. 1.

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

  2. 2.

    This vessel was identified and developed in the Marine Cybernetics Laboratory at Norwegian University of Science and Technology.

  3. 3.

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

  4. 4.

    For simplicity, the Coriolis matrix is neglected.

  5. 5.

    Safe distance, Ds is equal to the maximum length of a vessel’s hull.

  6. 6.

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

  7. 7.

    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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Correspondence to Ngo-Quoc-Huy Tran .

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Tran, NQH., Prodan, I., Phan, NDM. (2021). Collision-Free Path Following of an Autonomous Vehicle Using NMPC. In: Sattler, KU., Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H. (eds) Advances in Engineering Research and Application. ICERA 2020. Lecture Notes in Networks and Systems, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-030-64719-3_27

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  • DOI: https://doi.org/10.1007/978-3-030-64719-3_27

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-64719-3

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