Trajectory Planning for Multiple Vehicles Using Motion Primitives: A Moving Horizon Approach Under Uncertainty

Bahaaeldin Elsayed, Rolf Findeisen

2023

Abstract

Planning motion in cluttered and uncertain environments for autonomous systems remains a daunting challenge, especially when prioritizing safety and efficiency. This paper introduces an innovative method of melding motion primitives with a moving horizon strategy, drawing on the principles of model predictive control. Using motion primitives, we achieve simplified, high-level depictions of vehicle movement using various linear time-invariant models for each mode. This significantly cuts computational complexity in the subsequent planning stages. We integrate constraint backoff based on system uncertainties to ensure that generated trajectories are robust, collision-free, and adhere to all necessary constraints. This comprehensive framework produces optimal, safe trajectories that cater to environmental uncertainties and are suitable for real-time applications. Our simulation outcomes robustly highlight the strengths and distinctiveness of the proposed approach.

Paper Citation

in Harvard Style

Elsayed B. and Findeisen R. (2023). Trajectory Planning for Multiple Vehicles Using Motion Primitives: A Moving Horizon Approach Under Uncertainty. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5, SciTePress, pages 229-236. DOI: 10.5220/0012188700003543

in Bibtex Style

@conference{icinco23,
author={Bahaaeldin Elsayed and Rolf Findeisen},
title={Trajectory Planning for Multiple Vehicles Using Motion Primitives: A Moving Horizon Approach Under Uncertainty},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={229-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012188700003543},
isbn={978-989-758-670-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Trajectory Planning for Multiple Vehicles Using Motion Primitives: A Moving Horizon Approach Under Uncertainty
SN - 978-989-758-670-5
AU - Elsayed B.
AU - Findeisen R.
PY - 2023
SP - 229
EP - 236
DO - 10.5220/0012188700003543
PB - SciTePress