Vol. 17 / 2022 – International Conference on Virtual Learning
Applied learning of artificial intelligence techniques by using the Gazebo simulator and Turtlebot3 multi-robot system
Alexandru STAN, Mihaela OPREA
Robotics became an important educational testing resource for different methods and techniques, especially from the artificial intelligence domain. Thus, either classical artificial intelligence methods (such as planning and scheduling methods, informed search strategies, knowledge based systems, intelligent agents and multi-agent systems) or computational intelligent methods (such as artificial neural networks, genetic algorithms, swarm intelligence and nature-inspired algorithms) have been applied in different real world or simulated systems that were developed by using educational robots (e.g. Khepera, Turtlebot, Pioneer, Nomad, LegoMindStorm). Various educational robot’s simulation frameworks or integrated software tools have been developed so far (e.g. Webots, Gazebo, MiMicS, RoboNetSim). The paper focuses on some artificial intelligence techniques learned by using the Gazebo robot simulator and a Turtlebot3 multi-robot system. Details related to, for example, how is configured a multi-robot system, how is made the simulation of the multi-robot system are provided step by step in order to improve student learning process efficiency.
Keywords:
Robot simulator,
Educational robotics,
Multi-robot system configuration,
Artificial intelligence techniques
CITE THIS PAPER AS:
Alexandru STAN,
Mihaela OPREA,
"Applied learning of artificial intelligence techniques by using the Gazebo simulator and Turtlebot3 multi-robot system",
International Conference on Virtual Learning,
ISSN 2971-9291, ISSN-L 1844-8933,
vol. 17,
pp. 117-126,
2022.
https://doi.org/10.58503/icvl-v17y202210