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  1. Efficient arrangement of UAVs in a swarm formation is essential to the functioning of the swarm as a temporary communication network. Such a network could assist in search and rescue efforts by providing first responders with a means of communication. We propose a user-friendly and effective system for calculating and visualizing an optimal layout of UAVs. An initial calculation to gather parameter information is followed by the proposed algorithm that generates an optimal solution. A visualization is displayed in an easy-to-comprehend manner after the proposed iterative genetic algorithm finds an optimal solution. The proposed system runs iteratively, adding UAV atmore »each intermediate conclusion, until a solution is found. Information is passed between runs of the iterative genetic algorithm to reduce runtime and complexity. The results from testing show that the proposed algorithm yields optimal solutions more frequently than the k-means clustering algorithm. This system finds an optimal solution 80% of the time while k-means clustering is unable to find a solution when presented with a complex problem.« less
  2. Intelligent robot swarms are increasingly being explored as tools for search and rescue missions. Efficient path planning and robust communication networks are critical elements of completing missions. The focus of this research is to give unmanned aerial vehicles (UAVs) the ability to self-organize a mesh network that is optimized for area coverage. The UAVs will be able to read the communication strength between themselves and all the UAVs it is connected to using RSSI. The UAVs should be able to adjust their positioning closer to other UAVs if RSSI is below a threshold, and they should also maintain communication asmore »a group if they move together along a search path. Our approach was to use Genetic Algorithms in a simulated environment to achieve multi-node exploration with emphasis on connectivity and swarm spread.« less
  3. Efficient path planning and communication of multi-robot systems in the case of a search and rescue operation is a critical issue facing robotics disaster relief efforts. Ensuring all the nodes of a specialized robotic search team are within range, while also covering as much area as possible to guarantee efficient response time, is the goal of this paper. We propose a specialized search-and-rescue model based on a mesh network topology of aerial and ground robots. The proposed model is based on several methods. First, each robot determines its position relative to other robots within the system, using RSSI. Packets aremore »then communicated to other robots in the system detailing important information regarding robot system status, status of the mission, and identification number. The results demonstrate the ability to determine multi-robot navigation with RSSI, allowing low computation costs and increased search-and-rescue time efficiency.« less