Reinformcement lLearning pre riadenie robotov
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Vysoká škola báňská – Technická univerzita Ostrava
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Abstract
The goal of the work is to design and test methods for teaching robots to perform simple and more
complex tasks in the chosen simulator. CoppeliaSim with the PyRep and RPBench superstructure
can serve as the environment. The result of the work will be the functional integration of all parts
and the implementation of simpler algorithms to solve the submitted tasks
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Reinforced Learning, Deep Q-Learning, DDPG, Control of robots, Line Tracer