SUMMARYExploration is a fundamental problem in robotics, and multi-robot systems exploration has been extensively studied in this field. In order to overcome the problem of a non-optimal target being selected in the exploration process, a revised single linkage clustering frontier cell (CFC) algorithm is proposed to calculate the exploration benefit of all available frontier cells. Moreover, there exist unexplored islands for most of the bidding-based multi-robot coordination algorithms in the exploration of unknown environments. To deal with this problem, some rules switched by emotion states are proposed. So, the proposed bidding coordination algorithm with CFC and an emotion switch has a hierarchical architecture. The upper level is modeled as an automaton, which is used to represent emotion status, and the emotion variables decide whether a robot will participate in a bid and explore an unknown area abiding by the walking rules. In the lower level, the robots perform bidding activities with CFC and the walking rules according to the emotion variables. We tested and evaluated our approach by means of experiments both in a simulated environment and with real robots. The experiments results demonstrate that the exploration efficiency is improved, and our algorithm has a greater coverage rate than classic bidding-based coordination algorithms.