Multi-Robot Task Allocation for Inspection Problems with Cooperative Tasks Using Hybrid Genetic Algorithms

Liu, Chun

kassel university press, ISBN: 978-3-86219-551-0, 2014, 148 Seiten
(Schriftenreihe Mess- und Regelungstechnik der Universität Kassel 4)

Zugl.: Kassel, Univ., Diss. 2014

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Inhalt: In this dissertation, methods for optimal multi-robot task allocation (MRTA) for industrial plant inspection are investigated. MRTA involves distributing and scheduling a set of tasks for a group of robots to minimize the total cost taking into account operational constraints. With technical progress and declining cost of robotic mobility, interest in industrial mobile robotics has grown significantly in recent years. Many efforts have been devoted to mobility-related problems such as self-localization and mapping, though only few studies deal with the optimal task allocation in multi-robot systems. Since a good task allocation provides more efficient scheduling (e.g. less cost, shorter time), the objective of this research is to develop search/optimization methods for inspection problems that involve both single- and two-robot tasks.

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