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Cluster-based Multi-Robot Task Assignment, Planning, and Control
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-6762-7172
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3922-1735
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-1046-0305
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-8870-6718
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2024 (English)In: Article in journal (Other academic) Submitted
Place, publisher, year, edition, pages
2024.
National Category
Robotics
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-103890OAI: oai:DiVA.org:ltu-103890DiVA, id: diva2:1830545
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-01-24
In thesis
1. Synergistic Strategies in Multi-Robot Systems: Exploring Task Assignment and Multi-Agent Pathfinding
Open this publication in new window or tab >>Synergistic Strategies in Multi-Robot Systems: Exploring Task Assignment and Multi-Agent Pathfinding
2024 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Robots are increasingly utilized in industry for their capability to perform repetitive,complex tasks in environments unsuitable for humans. This surge in robotic applicationshas spurred research into Multi-Robot Systems (MRS), which aim to tackle complex tasksrequiring collaboration among multiple robots, thereby boosting overall efficiency. However,MRS introduces multifaceted challenges that span various domains, including robot perception,localization, task assignment, communication, and control. This dissertation delves into theintricate aspects of task assignment and path planning within MRS.The first area of focus is on multi-robot navigation, specifically addressing the limitationsinherent in current Multi-Agent Path Finding (MAPF) models. Traditional MAPF solutionstend to oversimplify, treating robots as holonomic units on grid maps. While this approachis impractical in real-world settings where robots have distinct geometries and kinematicrestrictions, it is important to note that even in its simplified form, MAPF is categorized as anNP-hard problem. The complexity inherent in MAPF becomes even more pronounced whenextending these models to non-holonomic robots, underscoring the significant computationalchallenges involved. To address these challenges, this thesis introduces a novel MAPF solverdesigned for non-holonomic, heterogeneous robots. This solver integrates the hybrid A*algorithm, accommodating kinematic constraints, with a conflict-based search (CBS) for efficientconflict resolution. A depth-first search approach in the conflict tree is utilized to accelerate theidentification of viable solutions.The second research direction explores synergizing task assignment with path-finding inMRS. While there is substantial research in both decentralized and centralized task assignmentstrategies, integrating these with path-finding remains underexplored. This dissertation evaluatesdecoupled methods for sequentially resolving task assignment and MAPF challenges. Oneproposed method combines the Hungarian algorithm and a Traveling Salesman Problem (TSP)solver for swift, albeit suboptimal, task allocation. Subsequently, robot paths are generatedindependently, under the assumption of collision-free navigation. During actual navigation, aNonlinear Model Predictive Controller (NMPC) is deployed for dynamic collision avoidance. Analternative approach seeks optimal solutions by conceptualizing task assignment as a MultipleTraveling Salesman Problem (MTSP), solved using a simulated annealing algorithm. In tandem,CBS is iteratively applied to minimize the cumulative path costs of the robots.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2024. p. 94
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
Keywords
Autonomous robots, Multi-robot systems, Task assignment, Multi-agent path-finding
National Category
Robotics
Research subject
Robotics and Artificial Intelligence
Identifiers
urn:nbn:se:ltu:diva-103895 (URN)978-91-8048-474-9 (ISBN)978-91-8048-475-6 (ISBN)
Presentation
2024-02-28, A117, Luleå University of Technology, Luleå, 09:00 (English)
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Supervisors
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-02-07Bibliographically approved

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Bai, YifanLindqvist, BjörnKarlsson, SamuelKanellakis, ChristoforosNikolakopoulos, George

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