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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| Author: | Julien Meine, Niklas Digakis, Niklas Dietz, Karol Rösner, Sarah Brüssing |
|---|---|
| URN: | urn:nbn:de:hbz:1010-opus4-43099 |
| Document Type: | video |
| Language: | German |
| Date of Publication (online): | 2023/02/02 |
| Date of first Publication: | 2023/02/02 |
| Publishing Institution: | Westfälische Hochschule Gelsenkirchen Bocholt Recklinghausen |
| Release Date: | 2024/01/26 |
| Departments / faculties: | Fachbereiche / Informatik und Kommunikation |
| Licence (German): |  Creative Commons - Namensnennung |
