Model Predictive Control for Crowd Navigation via Learning-Based Trajectory Prediction

Mohamed Parvez Aslam, Bojan Derajic, Bojan Derajic, Mohamed-Khalil Bouzidi, Mohamed-Khalil Bouzidi, Sebastian Bernhard, Jan Oliver Ringert

2025

Abstract

Safe navigation in pedestrian-rich environments remains a key challenge for autonomous robots. This work evaluates the integration of a deep learning-based Social-Implicit (SI) pedestrian trajectory predictor within a Model Predictive Control (MPC) framework on the physical Continental Corriere robot. Tested across varied pedestrian densities, the SI-MPC system is compared to a traditional Constant Velocity (CV) model in both open-loop prediction and closed-loop navigation. Results show that SI improves trajectory prediction-reducing errors by up to 76% in low-density settings-and enhances safety and motion smoothness in crowded scenes. Moreover, real-world deployment reveals discrepancies between open-loop metrics and closed-loop performance, as the SI model yields broader, more cautious predictions. These findings emphasize the importance of system-level evaluation and highlight the SI-MPC framework’s promise for safer, more adaptive navigation in dynamic, human-populated environments.

Paper Citation

in Harvard Style

Aslam M., Derajic B., Bouzidi M., Bernhard S. and Ringert J. (2025). Model Predictive Control for Crowd Navigation via Learning-Based Trajectory Prediction. In Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-770-2, SciTePress, pages 251-258. DOI: 10.5220/0013710400003982

in Bibtex Style

@conference{icinco25,
author={Mohamed Aslam and Bojan Derajic and Mohamed-Khalil Bouzidi and Sebastian Bernhard and Jan Ringert},
title={Model Predictive Control for Crowd Navigation via Learning-Based Trajectory Prediction},
booktitle={Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2025},
pages={251-258},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013710400003982},
isbn={978-989-758-770-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Model Predictive Control for Crowd Navigation via Learning-Based Trajectory Prediction
SN - 978-989-758-770-2
AU - Aslam M.
AU - Derajic B.
AU - Bouzidi M.
AU - Bernhard S.
AU - Ringert J.
PY - 2025
SP - 251
EP - 258
DO - 10.5220/0013710400003982
PB - SciTePress