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Automatic Planning of Collaborating Autonomous Unmanned Aerial Vehicles
Mälardalen University, School of Innovation, Design and Engineering.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Collaboration between autonomous robots allows for complex mission to be executed more eciently.A collaborative mission typically consists of a number of robots and tasks where the robots havedierent roles and need cooperatively assign the tasks to the team resulting in a faster overall missionexecution time. Furthermore, certain tasks may require more than one robot for successful executionwhich further extend the application areas of the systems.

In this work, a team of unmanned aircraft is considered. Aircraft operate in dynamic environmentswhere the conditions for the team can quickly change. Under such circumstances, the team mustbe able to independently update the current plan in real-time on embedded computers on-boardthe aircraft during mission execution in a fast and predictable manner. The planning system has togenerate good quality solutions and fulll certain application specic requirements set by the company.

The work starts by presenting a limited structured literature review within the multi-agent taskplanning domain with specic focus on important criteria for the aircraft domain, namely real-timeperformance, connectivity requirements and solution quality. With the review as a basis, two marketbased approaches are modied and extended upon the handle the application specic requirements.Simulations show that the resulting systems produce good quality and conict free plans regardless ofinconsistencies in situational awareness among the aircraft. The two approaches are numerically analyzedwith respect to the above-mentioned criteria, and show promising results for real-time planningand replanning in dynamic environments.

Place, publisher, year, edition, pages
2016. , p. 51
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-32123OAI: oai:DiVA.org:mdh-32123DiVA, id: diva2:940487
External cooperation
Saab AB
Subject / course
Computer Science
Supervisors
Examiners
Available from: 2017-10-17 Created: 2016-06-21 Last updated: 2018-01-10Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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Output format
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