Adaptive robot formations using fast marching square working under uncertainty conditions

Robot formations are getting important since they can develop tasks that only one robot could not do or could take too much time. Also, they can perform some tasks better than humans. This paper provides a new algorithm to control robot formations working under uncertainty conditions such as errors in robot positions, errors when sensing obstacles or walls, etc. The proposed approach provides a robust solution based on leader-followers architecture (real or virtual leaders) with a prescribed geometry of the formation and it adapts dynamically to the environment. The algorithm applies the Fast Marching Square (FM2) method to the path planning of mobile robot formations, which have been proved to work fast and efficiently. The FM2 method is a potential based path planning method with no local minima which provides smooth and safe trajectories. The algorithm described here allows to easily set different behaviours to the formation during its motion depending on the objectives, being possible to set its flexibility. The results presented here show that using this method allows to the formation reacting to either static and dynamic obstacles with an easily changeable behaviour.