Collaboration between several Unmanned Aerial Vehicles (UAVs) can produce high-quality results in numerous missions, including surveillance, search and rescue, tracking or identification. Such a combination of collaborative UAVs is referred to as a swarm. These several platforms enhance the global system capabilities by supporting some form of resilience and by increasing the number and/or the variety of the embedded sensors. Furthermore, several UAVs organized in a swarm can (should the ground control station support this) be considered as a single entity from an operator point-of-view. We aim at using such swarms in complex and unknown environments, and in the long term, allow compact flights.Dynamic path planning computation for each UAV is a major task to perform their mission. To define this path planning, we have implemented a three-dimensional (3D) mobility model for swarms of UAVs using both the Artificial Potential Fields (APF) principle and a global path planning method. In our model, the collaboration between the platforms is made by sharing information about the detected obstacles. To provide a significant validation of our mobility model, we have simulated real-world environments and real-world sensors characteristics, using the OMNeT + network simulator.
A 3D Mobility Model for Autonomous Swarms of Collaborative UAVs
2019-06-01
2467930 byte
Conference paper
Electronic Resource
English
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