Communication-aware distributed PSO for dynamic robotic search

The use of swarm robotics in search tasks is an active area of research. A variety of algorithms have been developed that effectively direct robots toward a desired target by leveraging their collaborative sensing capabilities. Unfortunately, these algorithms often neglect the task of communicating possible task solutions outside of the swarm. Many scenarios require a monitoring station that must receive updates from robots within the swarm. This task is trivial in constrained locations, but becomes difficult as the search area increases and communication between nodes is not always possible. A second shortcoming of existing algorithms is the inability to find and track mobile targets. We propose an extension to the distributed Particle Swarm Optimization algorithm that is both communication-aware and capable of tracking mobile targets within a search space. Simulated experiments show that our algorithm returns more accurate solutions to a monitoring station than existing algorithms, especially in scenarios, where the target value or location changes over time.