Fault-Tolerant Flocking in a k-Bounded Asynchronous System
This paper studies the flocking problem, where mobile robots group to form a desired pattern and move together while maintaining that formation. Unlike previous studies of the problem, we consider a system of mobile robots in which a number of them may possibly fail by crashing. Our algorithm ensures that the crash of faulty robots does not bring the formation to a permanent stop, and that the correct robots are thus eventually allowed to reorganize and continue moving together. Furthermore, the algorithm makes no assumption on the relative speeds at which the robots can move.
The algorithm relies on the assumption that robots’ activations follow a k-bounded asynchronous scheduler, in the sense that the beginning and end of activations are not synchronized across robots (asynchronous), and that while the slowest robot is activated once, the fastest robot is activated at most k times (k-bounded).
The proposed algorithm is made of three parts. First, appropriate restrictions on the movements of the robots make it possible to agree on a common ranking of the robots. Second, based on the ranking and the k-bounded scheduler, robots can eventually detect any robot that has crashed, and thus trigger a reorganization of the robots. Finally, the third part of the algorithm ensures that the robots move together while keeping an approximation of a regular polygon, while also ensuring the necessary restrictions on their movement.
KeywordsMobile Robot Failure Detection Regular Polygon Autonomous Mobile Robot Half Circle
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