Multi-robot exploration with communication requirement to a moving base station

Exploration is a core and important robotics area, whose applications include search and rescue robotics, planetary exploration etc. We know that this exploration task is best performed when using a multi-robot system. In this paper, we present an algorithm for multi-robot exploration of an unknown environment, taking into account the communication constraints between the robots. The aim of the robots is to explore the whole map as a pack, without losing communication throughout. The key task for us here is to allocate the target points for multiple robots so as to maximize the area explored and minimize the time and plan paths for the robots in such a way so as to avoid obstacles. A multi-robot exploration methodology is introduced similar to depth first strategy, that samples frontier points based on a metric function. This function aims to maximize the visibility gain or information gain while minimizing the distance to be travelled to the frontier points, such that the robots are within the limited communication distance of each other. The algorithm has been tested through simulation runs of various maps and results and evaluations have been presented based on it. The results effectively demonstrate that our algorithm allows robot pack to quickly accomplish the task of exploration and without the constraint ever breaking down. Here, we also present a comparative analysis of our algorithm with another exploration approach, which finds new areas based on population generation and utility calculation over the population. The results show tangible performance gain of this method over previous methods reported on exploration with limited communication constraints.