Jezik: | Slovenski jezik |
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Leto izida: | 2020 |
Tipologija: | 2.09 - Magistrsko delo |
Organizacija: | UL FS - Fakulteta za strojništvo |
Založnik: | [M. Knap] |
UDK: | 007.52:519.8:004.8(043.2) |
COBISS: | 38621699 |
Št. ogledov: | 358 |
Št. prenosov: | 74 |
Ocena: | 0 (0 glasov) |
Metapodatki: |
Sekundarni jezik: | Angleški jezik |
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Sekundarni naslov: | Reinforcement learning-based task assignment in a mobile robot system |
Sekundarni povzetek: | Modern logistic solutions encompass the use of mobile robot systems. To achieve a successful implementation of such a system, one must consider an efficient design of transportation task assignment system. Main responsibility of a task assignment system is to allocate tasks in such manner that as many tasks get completed in a given time frame. This problem is recognized as a multicriteria optimization problem. The purpose of this thesis is to develop a task assignment algorithm that is based on reinforcement learning. The proposed algorithm was developed using ROS platform. We developed an algorithm with an emphasis on fast learning. The proposed algorithm was tested in a simulated environment. It was tested alongside simple task assignment rules that meet only single criterion of an assignment problem. Every task assignment algorithm was tested in an hour long experiment. Robots managed to complete the highest number of tasks in the case of the developed solution. Measurements of traveled distances and task completion times confirmed the one-sided decisions of simple rules, and the multicriteria decision-making process of the developed algorithm. |
Sekundarne ključne besede: | master thesis;robotics;optimization;reinforcement learning;task assignment;mobile robot system;ROS platform; |
Vrsta dela (COBISS): | Magistrsko delo/naloga |
Študijski program: | 0 |
Konec prepovedi (OpenAIRE): | 1970-01-01 |
Komentar na gradivo: | Univ. Ljubljana, Fak. za strojništvo |
Strani: | XXIV, 75 str. |
ID: | 12114464 |