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Adaptive Autonomy in a Search and Rescue Scenario
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. (Robotics)ORCID-id: 0000-0001-7852-4582
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. (Robotics)ORCID-id: 0000-0002-5224-8302
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. (Robotics)ORCID-id: 0000-0002-5832-5452
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1364-8127
2018 (engelsk)Inngår i: International Conference on Self-Adaptive and Self-Organizing Systems, SASO, Volume 2018-September, 15 January 2019, 2018, s. 150-155Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Adaptive autonomy plays a major role in the design of multi-robots and multi-agent systems, where the need of collaboration for achieving a common goal is of primary importance. In particular, adaptation becomes necessary to deal with dynamic environments, and scarce available resources. In this paper, a mathematical framework for modelling the agents' willingness to interact and collaborate, and a dynamic adaptation strategy for controlling the agents' behavior, which accounts for factors such as progress toward a goal and available resources for completing a task among others, are proposed. The performance of the proposed strategy is evaluated through a fire rescue scenario, where a team of simulated mobile robots need to extinguish all the detected fires and save the individuals at risk, while having limited resources. The simulations are implemented as a ROS-based multi agent system, and results show that the proposed adaptation strategy provides a more stable performance than a static collaboration policy. 

sted, utgiver, år, opplag, sider
2018. s. 150-155
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-40254DOI: 10.1109/SASO.2018.00026ISI: 000459885200016Scopus ID: 2-s2.0-85061910844ISBN: 9781538651728 (tryckt)OAI: oai:DiVA.org:mdh-40254DiVA, id: diva2:1233552
Konferanse
12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2018; Trento; Italy; 3 September 2018 through 7 September 2018
Tilgjengelig fra: 2018-07-18 Laget: 2018-07-18 Sist oppdatert: 2020-05-07bibliografisk kontrollert
Inngår i avhandling
1. Collaborative Adaptive Autonomous Agents
Åpne denne publikasjonen i ny fane eller vindu >>Collaborative Adaptive Autonomous Agents
2018 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
sted, utgiver, år, opplag, sider
Mälardalen University Press, 2018
Serie
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 271
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-40255 (URN)978-91-7485-399-5 (ISBN)
Presentation
2018-09-14, Gamma, Mälardalens högskola, Västerås, 09:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2018-07-19 Laget: 2018-07-18 Sist oppdatert: 2019-10-01bibliografisk kontrollert
2. Modelling and Control of the Collaborative Behavior of Adaptive Autonomous Agents
Åpne denne publikasjonen i ny fane eller vindu >>Modelling and Control of the Collaborative Behavior of Adaptive Autonomous Agents
2020 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Västerås: Mälardalen University, 2020
Serie
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 314
HSV kategori
Forskningsprogram
datavetenskap
Identifikatorer
urn:nbn:se:mdh:diva-47905 (URN)978-91-7485-468-8 (ISBN)
Disputas
2020-06-12, Västerås Campus (+ Online/Zoom), Mälardalens högskola, Västerås, 10:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2020-05-08 Laget: 2020-05-06 Sist oppdatert: 2020-05-13bibliografisk kontrollert

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