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EN
The issue of coordinated operation of multi-vehicle for a variety of tasks is getting increasing attention day by day and standing as a major research field due to their increased capacity and flexibility they can offer as a team. This paper presents a novel algorithm for multi-vehicle navigation, based on exhaustive search to avoid a set of randomly generated obstacles, predict the approximate position of other vehicles and thus keeping a safe distance to avoid collision and to maintain a formation amongst them while targeted towards the assigned goals. The proposed algorithm uses two optimizing functions in deriving drive commands, direction and turning, for a troop of vehicles. This particular algorithm is similar to the artificial potential field (APF) method which is widely used for autonomous mobile robot path planning due to its simplicity and mathematical elegance. In this work we have taken a behavior based reactive scheme together with artificially generated perturbation as the vehicles are running in a real time environment. Simulations have been carried out for a group of four vehicles, paired in two groups, approaching two different targets avoiding eight randomly generated obstacles, and keeping proper coordination between the members of intra and inter groups. The effectiveness of the proposed approach has been shown by some simulation results.
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