Multi-Sensor-Based Predictive Control for Autonomous Parking in Presence of Pedestrians

David Pérez-Morales (1, 2) , Olivier Kermorgant (1, 2) , Salvador Domínguez-Quijada (1, 2) , Philippe Martinet (3, 1)

1 ECN - École Centrale de Nantes
2 LS2N - Laboratoire des Sciences du Numérique de Nantes
3 CRISAM - Inria Sophia Antipolis - Méditerranée

This paper explores the feasibility of a Multi-Sensor-Based Predictive Control (MSBPC) approach in order to have constraint-based backward non-parallel (perpendicular and diagonal) parking maneuvers capable of dealing with moving pedestrians and, if necessary, performing multiple maneuvers. Our technique relies solely in sensor data expressed relative to the vehicle and therefore no localization is inherently required. Since the proposed approach does not plan any path and instead the controller maneuvers the vehicle directly, the classical path planning related issues are avoided. Real experimentation validates the effectiveness of our approach.

Domaines: Robotique [cs.RO]

David Pérez-Morales, Olivier Kermorgant, Salvador Domínguez-Quijada, Philippe Martinet. Multi-Sensor-Based Predictive Control for Autonomous Parking in Presence of Pedestrians. ICARCV 2020 - 16th International Conference on Control, Automation, Robotics and Vision, Dec 2020, Shenzhen, China. ⟨hal-02933694⟩