PSO algorithm for mobile robots deployment by cooperative transmission technology

We research on mobile robots network deployment which do cooperative transmission (CT) in diversity configuration along a strip line to expand the transmission range. The emphasis is on optimal the clusters of the robots and the locations of the clusters to maximize the multi-hop robots network reach along a straight line based on the particle swarm optimization (PSO) algorithm. Every mobile robot was considered as a bird, and fly toward the food source. Firstly, the initial deployment place of nodes is set randomly. Then, the velocity of movement is determined under the constraint of outage probability and velocity update rule function. Finally, the deployment of the cluster robots is finished by many times iteration to achieve the optimal point. In order to avoid missing peak value, we improved the velocity, particle-self and global particle experience function. The simulation results show that this deployment model is effective to get the maximum range expansion. PSO algorithm has characteristics such as high precision and time saving, PSO have a better performance than ACS and EAM.