Robotics, the branch which is completely dedicated to the field of Electronics and Computer Science Engineering is now being connected to Artificial Intelligence for several purposes. Such robots are being connected for playing soccer via Artificial Intelligence. This event is called Robocup. There is a wide competition every year among researchers to present their robots at the Robocup Challenge.
There was an introduction of Pyrus, which was a Python-based platform for the simulation of Robocup. Researchers from Dalhousie University and Memorial University of Canada published a research paper in which they mentioned that they would train and test the model using Pyrus easily. The common frameworks used for the Robocup were HeliosBase and Cyrus2DBase. These frameworks used their primary language C++. These frameworks had advantages over others as C++ is used for many instances, as it is more advanced and wide compared to Python. Researchers are also working on building a better framework that will be completely based on Python. This framework can be diversified and can be used by a wide range of users with different technical experiences and skills. Frameworks like Tensorflow, Keras, and PyTorch are used in base code to a large extent. A framework such as Pyrus implements C++base code easily. The main advantage of Pyrus over other frameworks is that it is simple and accessible so even beginners can also test their models for the Robocup league. The main problem is that the environment for Robocup is a bit noisy. To tackle this problem, researchers implemented Reinforcement Learning and Machine Learning models such as dribbling or passing. This reduced the noise to some extent as they had noise cancellation ability.
The Robocup has introduced all the data enthusiasts to solve all Data Analytics problems to a larger extent. Researchers have also introduced Pyrus to solve basic Machine Learning Challenges related to Robocup. Researchers are still working on the Pyrus base code to improve its performance. Researchers also plan to implement a Python monitor and log analysis software to improve the feasibility of the model to a larger extent.
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