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Multi-robot formations for area coverage in space applications
2009 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis presents two algorithmic implementations of multi-robot formation control for the area coverage problem. It uses a space exploration scenario, with a marsupial robot society, for tasks like mapping, habitat construction, etc. The solutions are though applicable to a wider range of applications, since area coverage is seen as one of the canonical problems in multi-robot application. Starting with an overview of multi-robot systems in space applications, both currently in use and planned for the near future, it then presents the two algorithms and their implementation in C++: (i) a vector force based implementation and (ii) a machine learning approach. The second is based on an organizational-learning oriented classifier system (OCS) introduced by Takadama an evolution of Holland’s learning classifier system (LCS). To ease the development, testing and evaluation of the control algorithms a simulator, named SMRTCTRL, was implemented during a 3 months research stay at the University of Tokyo. The vector-based control approach was tested using a multi-robot society of LEGO Mindstorms Robots and a comparison of the two algorithm was done with the help of the simulator.

Place, publisher, year, edition, pages
Keyword [en]
Technology, space robotics, multi-robot cooperation, area coverage, machine learning, simulation, formation control, Learning, Classifier Systems (LCS)
Keyword [sv]
URN: urn:nbn:se:ltu:diva-51410ISRN: LTU-PB-EX--09/075--SELocal ID: 89a60435-f45c-4b54-8311-91f76a8019fdOAI: diva2:1024771
Subject / course
Student thesis, at least 30 credits
Educational program
Space Engineering, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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