Telefonaktiebolaget Lm Ericsson (Publ)

Dhiraj Nagaraja Hegde

Kaushik Dey

Abhishek Sarkar

Ashis Kumar Roy

A method manages a group of Unmanned Aerial Vehicles (UAVs) operable to fly in a formation. Each UAV is programmed with a task to be performed by the UAV. The method is performed in a controller UAV of the group and comprises receiving UAV status information from UAVs in the group, obtaining information on a current formation of the group and combining the received UAV status information with the information on current group formation to form a representation of a first state of the group. A machine learning model is used to predict, based on the first state of the group, an optimal formation transition to a new formation and to instruct the UAVs in the group to perform the predicted optimal formation transition, which is a transition to a formation that will minimise predicted total energy consumption for all UAVs in the group to complete their tasks.

Formation flight of unmanned aerial vehicles

It is provided a method for adjusting alignment for microwave transmissions from a microwave transmitter to a microwave receiver based on a reinforcement learning, RL, model. The method comprises the steps of: obtaining state space comprising external state space and internal state space, the external state space comprising at least one value of a parameter related to environmental conditions, and the internal state space relates to alignment of the microwave transmitter; determining an action in an action space, the action space comprising actions to adjust alignment of the microwave transmitter; obtaining a measurement of path loss for a transmission from the microwave transmitter to the microwave receiver; determining a reward value based on the path loss, wherein an increase in path loss results in a reduced reward value; and adjusting the RL model based on the obtained state space, the determined action and the determined reward value.

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Bengaluru, India

Dhiraj Nagaraja Hegde