Neural network to study crowd physics for training urban robots

Robotics Business Review

The chaotically moving objects dense clusters digital twin is being developed by students from NUST MISIS, ITMO and MIPT to navigate robots. It is going to be a web service using graph neural networks, which will allow studying the physics of crowds, the laws of swarm behavior in animals and the principles of “active matter” motion. This data is often required for educating courier robots, drones and other autonomous devices operating in crowded spaces. The first results were published in the Journal of Physics: Conference Series.
Source: techxplore

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