Multi-robot formations for area coverage in space applications
No Thumbnail Available
URL
Journal Title
Journal ISSN
Volume Title
Master's thesis
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
2009
Department
Major/Subject
Automaatiotekniikka
Mcode
Aut-84
Degree programme
Language
en
Pages
99
Series
Abstract
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.Description
Supervisor
Halme, AarneHyyppä, Kalevi
Thesis advisor
Nakasuka, ShinichiTaipalus, Tapio
Keywords
space robotics, multi-robot cooperation, area coverage, machine learning, simulation, formation control, Learning Classifer Systems, LCS