Nanorobots target search strategies using swarm intelligence

Controlling a swarm of bee-like nanorobots in search of a target in a human body-like environment is a challenge. The challenge lies in the causal factors of emergence. This research focused on designing and developing a bee-inspired algorithm to provide instructions to coordinate simple and naïve nanorobots in search of a target. Experiments were conducted through simulations to determine the rate at which myriads of agents converge at a target. A maze environment depicting human blood vessels was used to deploy the nanorobots. Different sample population sizes were used, and the results indicate that the bigger the sample size, the higher the convergence speed. Compared with a single complicated robot, the swarm of intelligently controlled nanorobots proved efficient and effective in finding a target in a human-like environment.