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An algorithm for distributed exploration in 3D is presented which always keeps the robots within communication range of each other. The method is based on a greedy optimization strategy that uses a heuristic utility function. This makes it computationally very efficient but it can also lead to local minimums; but related deadlocks can be easily detected during the exploration process and there is an efficient strategy to recover from them. The exploration algorithm is integrated into a complete control infrastructure for Autonomous Underwater Vehicles (AUV) containing sensors, mapping, navigation, and control of actuators. The algorithm is tested in a high fidelity simulator which takes into account the dynamics of the robot, and simulates the required sensors. The effect of the communication range and the number of robots on the algorithm is investigated.

A Distributed Algorithm for Cooperative 3D Exploration under Communication Constraints