Congestion Prediction for Large Fleets of Mobile Robots
Ge Yu,Michael T. Wolf,Ge Yu,Michael T. Wolf
This paper introduces a deep learning (DL) approach to predicting congestion delays in large multi-robot systems. The problem is motivated by real-world problems in modern logistics automation, such as a warehouse with hundreds to thousands of coordinated mobile robots. Here, the large scale, the complexity of the control software, and the uncertainties of the robots' dynamics make direct (simulat...
