Abstract
Interference and jamming become crucial issues in swarm robot communication and sensing, especially in underwater applications. In this paper, an algorithm for facilitating scheduling within robotic swarm is formulated and its investigation in a series of experiments is described. The scheduling algorithm is biologically inspired by the firefly and frog. Novel distributed models for both algorithms are also investigated to improve scalability and provide decentralization of the algorithms. It is proven from the simulated experiments that the model is robust and viable for scheduling underwater swarm communication and sensing. Moreover, the paper illustrates that global swarm cognition can also be achieved using the algorithm to estimate the swarm density in a decentralized way. Finally, a real robot experiment using underwater swarm robot platforms is also presented.
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