Birds and UAVs (Unmanned Aerial Vehicles) are able to fly continuously large distances taking advantage of conditions of the environment. The main goal is to use thermals - rising masses of hot air, forming usually over warm areas, e.g. rocks or roofs. Agents climb on thermals and sink in chosen direction to save energy and stay in the air. Speed of a flight of an agent depend on the environment. One of the important features is density of thermals - enabling agents to reach next thermal after gliding down from previous one. What is more, position of thermals can change over time, due to wind or temperature fluctuations. Adjusting speed and move direction to environmental conditions can extend duration of flight and save the energy of an agent.

On the other hand, it is difficult to predict the environment and position of thermals. While reaching a next thermal by a single UAV is possible in favorable conditions, it is much easier to continue flight in a swarm of communicating UAVs. Sending information of a current  thermal position to other UAVs extends their knowledge of the environment what results in increase of an average speed of the swarm. What is more, the patterns of UAVs paths change -  their tend to form groups of different size and range. Grouping, speed and percolation effect depend on a number of UAVs and communication range adjusted to environment conditions. Here we present a model for the swarm of communicating UAVs in changing environment with focus on flight characteristics in given conditions.

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