Dynamic Peloton Formation Configuration Algorithm of Swarm Robots for Aerodynamic Effects Optimization

This paper presents a flocking and formation algorithm adapted from the flocking behavior of cycling team or pelotons. Several multi agent applications require efficient positioning of the agents in static and dynamic tasks. It was verified physically that an optimal distance in a peloton formation, the agents take reduced drag due to the inherent drag resistant characteristic of the formation. The said conditions were implemented in an algorithm in a swarm of wheeled robots. Experiment results show that the optimal distance between agents were attained. It was shown that the adaptation of peloton behavior in artificial agents brought efficient formation and foraging trajectories and behaviors.