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Modeling the willingness to interact in cooperative multi-robot systems
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-7852-4582
Aarhus Universitet, Aarhus, Denmark.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1364-8127
2020 (English)In: ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence, VOL 1, SciTePress , 2020, Vol. 1, p. 62-72Conference paper, Published paper (Refereed)
Abstract [en]

When multiple robots are required to collaborate in order to accomplish a specific task, they need to be coordinated in order to operate efficiently. To allow for scalability and robustness, we propose a novel distributed approach performed by autonomous robots based on their willingness to interact with each other. This willingness, based on their individual state, is used to inform a decision process of whether or not to interact with other robots within the environment. We study this new mechanism to form coalitions in the on-line multiobject κ-coverage problem, and compare it with six other methods from the literature. We investigate the trade-off between the number of robots available and the number of potential targets in the environment. We show that the proposed method is able to provide comparable performance to the best method in the case of static targets, and to achieve a higher level of coverage with respect to the other methods in the case of mobile targets.

Place, publisher, year, edition, pages
SciTePress , 2020. Vol. 1, p. 62-72
Keywords [en]
Adaptive Autonomy, Robot Collaboration, κ-Coverage Problem
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-47559DOI: 10.5220/0008951900620072ISI: 000570767700005Scopus ID: 2-s2.0-85083267753ISBN: 9789897583957 (print)OAI: oai:DiVA.org:mdh-47559DiVA, id: diva2:1425978
Conference
12th International Conference on Agents and Artificial Intelligence, ICAART 2020; Valletta; Malta; 22 February 2020 through 24 February 2020; Code 158715
Available from: 2020-04-23 Created: 2020-04-23 Last updated: 2022-11-08Bibliographically approved
In thesis
1. Modelling and Control of the Collaborative Behavior of Adaptive Autonomous Agents
Open this publication in new window or tab >>Modelling and Control of the Collaborative Behavior of Adaptive Autonomous Agents
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Research on autonomous agents and vehicles has gained momentum in the past years, which is reflected in the extensive body of literature and the investment of big players of the industry in the development of products such as self-driving cars. Additionally, these systems are envisioned to continuously communicate and cooperate with one another in order to adapt to dynamic circumstances and unforeseeable events, and as a result will they fulfil their goals even more efficiently.The facilitation of such dynamic collaboration and the modelling of interactions between different actors (software agents, humans) remains an open challenge.This thesis tackles the problem of enabling dynamic collaboration by investigating the automated adjustment of autonomy of different agents, called Adaptive Autonomy (AA). An agent, in this context, is a software able to process and react to sensory inputs in the environment in which it is situated in, and is additionally capable of autonomous actions. In this work, the collaborative adaptive autonomous behaviour of agents is shaped by their willingness to interact with other agents, that captures the disposition of an agent to give and ask for help, based on different factors that represent the agent's state and its interests.The AA approach to collaboration is used in two different domains: (i) the hunting mobile search problem, and (ii) the coverage problem of mobile wireless sensor networks. In both cases, the proposed approach is compared to state-of-art methods.Furthermore, the thesis contributes on a conceptual level by combining and integrating the AA approach -- which is purely distributed -- with a high-level mission planner, in order to exploit the ability of dealing with local and contingent problems through the AA approach, while minimising the requests for a re-plan to the mission planner.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2020
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 314
National Category
Engineering and Technology Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-47905 (URN)978-91-7485-468-8 (ISBN)
Public defence
2020-06-12, Västerås Campus (+ Online/Zoom), Mälardalens högskola, Västerås, 10:00 (English)
Opponent
Supervisors
Available from: 2020-05-08 Created: 2020-05-06 Last updated: 2022-11-08Bibliographically approved

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Frasheri, MirgitaPapadopoulos, Alessandro

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