Decentralized control of a heterogeneous human-robot team for exploration and patrolling - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles IEEE Transactions on Automation Science and Engineering Year : 2022

Decentralized control of a heterogeneous human-robot team for exploration and patrolling

Abstract

We present a decentralized connectivity-maintenance control framework for an heterogeneous human-robot team. The algorithm is able to manage a team composed of an arbitrary number of mobile robots (drones and ground robots in our case) and humans, for collaboratively achieving exploration and patrolling tasks. Differently from other works on the subject, here the human user physically becomes part of the team, moving in the same environment of the robots and receiving information about the team connectivity through wearable haptics or audio feedback. While the human explores the environment, the robots move so as to keep the team connected via a connectivity-maintenance algorithm; at the same time, each robot can also be assigned with a specific target to visit. We carried out three hu- man subject experiments, both in virtual and real environments. Results show that the proposed approach is effective in a wide range of scenarios. Moreover, providing either haptic or audio feedback for conveying information about the team connectivity significantly improves the performance of the considered tasks, although users significantly preferred receiving haptic stimuli w.r.t. the audio ones.
Fichier principal
Vignette du fichier
Aggravi-TASE-21.pdf (1.34 Mo) Télécharger le fichier
AgSiRoPa-TASE-2020.mp4 (34.24 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Licence : CC BY - Attribution
Licence : CC BY - Attribution

Dates and versions

hal-03321834 , version 1 (18-08-2021)

Licence

Attribution

Identifiers

Cite

Marco Aggravi, Giuseppe Sirignano, Paolo Robuffo Giordano, Claudio Pacchierotti. Decentralized control of a heterogeneous human-robot team for exploration and patrolling. IEEE Transactions on Automation Science and Engineering, 2022, 19 (4), pp.3109-3125. ⟨10.1109/TASE.2021.3106386⟩. ⟨hal-03321834⟩
142 View
624 Download

Altmetric

Share

Gmail Facebook X LinkedIn More