The problem of finding a target and forming a path to it is known and is well-explored in the field of swarm robotics. Using swarm intelligence, even swarms of simple robots are capable of solving this problem. However, often these works assume that two robots can perceive each o
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The problem of finding a target and forming a path to it is known and is well-explored in the field of swarm robotics. Using swarm intelligence, even swarms of simple robots are capable of solving this problem. However, often these works assume that two robots can perceive each other can physically reach each other, or that robots can detect any target within communication range. These assumptions do not hold for all swarms and environments. This thesis introduces the CSP (Concurrent Searching and Pathfinding) algorithm to make path finding possible in simple swarms without relying on these assumptions. By strategically constructing and reconstructing an ephemeral network of stationary robots and relocating the rest of the robots throughout this network, swarms performing CSP can efficiently find targets with minimal risk of fracturing the network. The effect of packet loss, and swarm size, as well as the the execution time vis-à-vis creation of new anchors are shown.