State-Aware Path-Following with Humans Through Force-based Communication via Tethered Physical Aerial Human-Robot Interaction - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

State-Aware Path-Following with Humans Through Force-based Communication via Tethered Physical Aerial Human-Robot Interaction

Résumé

The area of Aerial Physical Interaction has seen significant advancements, creating the opportunity for aerial robots to physically interact with humans. Our previous works established a framework for safe, human-aware path guidance via a tether, physically connecting a human to an aerial vehicle. However, the previous controller is purely reactive and does not leverage modern path-following methods. Further, its design does not properly account for the non-holonomic nature of the tethered human-robot system. In this paper we improved performance by addressing both problems. First, we incorporate modern path-following methods into our guidance framework to account for path geometry and current system velocity. Second, we propose a polar parametrization of the guidance law to achieve faster convergence of the guidance force to the desired value. Finally, the performance and human comfort of the different extensions is evaluated in simulation. The final method is shown to increase guidance accuracy and comfort, thereby increasing the usefulness of guidance via aerial robot interaction.
Fichier principal
Vignette du fichier
main.pdf (2.49 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04174537 , version 1 (01-08-2023)

Licence

Paternité

Identifiants

Citer

Ben Hallworth, Mike Allenspach, Roland Siegwart, Marco Tognon. State-Aware Path-Following with Humans Through Force-based Communication via Tethered Physical Aerial Human-Robot Interaction. ICUAS 2023 - International Conference on Unmanned Aircraft Systems, Jun 2023, Warsaw, Poland. pp.183-190, ⟨10.1109/ICUAS57906.2023.10155970⟩. ⟨hal-04174537⟩
7 Consultations
2 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More