Model Predictive Control for Dynamic Quadrotor Bearing Formations - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Model Predictive Control for Dynamic Quadrotor Bearing Formations

Résumé

Formation control of multi-agent systems deals with groups of robots forming specific spatial geometries. Combined with the advancements of unmanned aerial vehicles (UAVs) in the past decade, formation control may potentially be applied to tasks such as search-and-rescue, surveillance, even collaborative manipulation. A key challenge is the decentralization of formation control, where each agent behaves independently using onboard sensors and computation, improving the scaleability and robustness of the system. This paper proposes a decentralized controller based on model predictive control (MPC), for the control of formations of quadrotor UAVs defined by inter-agent bearings. The use of MPC allows the controller to account for attitude kinematics, improving upon the results of existing bearing formation control methods based on rigidity and visual servoing approaches, which typically only consider the quadrotor as a single or double integrator. Furthermore the near-optimality of MPC permits a more optimal use of the quadrotors dynamic capabilities for faster maneuvering. Extensive simulations are performed to demonstrate the improved transient formation convergence and fast maneuvering permitted by this controller. Experiments show that it is indeed a real-time feasible solution for bearing formation control.
Fichier principal
Vignette du fichier
MPC_ICRA_preprint.pdf (3.97 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03177635 , version 1 (23-03-2021)

Identifiants

  • HAL Id : hal-03177635 , version 1

Citer

Julian Erskine, Rafael Balderas-Hill, Isabelle Fantoni, Abdelhamid Chriette. Model Predictive Control for Dynamic Quadrotor Bearing Formations. IEEE International Conference on Robotics and Automation, May 2021, Xi'an (virtual), China. ⟨hal-03177635⟩
197 Consultations
360 Téléchargements

Partager

Gmail Facebook X LinkedIn More