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RobSwarm: Deep reinforcement multi robot mapping

  • Problem: A group of robots, called a swarm, is placed in an unknown environment and is supposed to explore it independently. The goal of the exploration is the creation of a common map. Implementation - Equipping six Kobuki robots with appropriate sensor technology, a large battery, a router and the Jetson board - Setup of the Jetson-Boards with self-made ROS2 nodes and the set up mesh network - Writing of launch files for the common start of all functions - Reinforcement learning is used to train an AI that controls the swarm by selecting points for the robots to approach and navigating to them and navigating them there. - Setting up a responsive website using Angular and the Bootstrap Framework.

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  • Problem: A group of robots, called a swarm, is placed in an unknown environment and is supposed to explore it independently. The goal of the exploration is the creation of a common map. Implementation - Equipping six Kobuki robots with appropriate sensor technology, a large battery, a router and the Jetson board - Setup of the Jetson-Boards with self-made ROS2 nodes and the set up mesh network - Writing of launch files for the common start of all functions - Reinforcement learning is used to train an AI that controls the swarm by selecting points for the robots to approach and navigating to them and navigating them there. - Setting up a responsive website using Angular and the Bootstrap Framework.

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Metadaten
Verfasserangaben:Julien Meine, Niklas Digakis, Niklas Dietz, Karol Rösner, Sarah Brüssing
URN:urn:nbn:de:hbz:1010-opus4-43099
Dokumentart:Video
Sprache:Deutsch
Datum der Veröffentlichung (online):02.02.2023
Datum der Erstveröffentlichung:02.02.2023
Veröffentlichende Institution:Westfälische Hochschule Gelsenkirchen Bocholt Recklinghausen
Datum der Freischaltung:26.01.2024
Fachbereiche / Institute:Fachbereiche / Informatik und Kommunikation
Lizenz (Deutsch):License LogoCreative Commons - Namensnennung

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