On The Virtual Market Based Approach For Environment Exploration Of Multi-robot Systems

In order to improve the efficiency of multi-robot exploration, we need to make the robots dispersed in the environment as far as possible. To solve this problem, this paper combines the artificial potential field theory and the virtual market mechanism. Virtual market is used to coordinate robots so that they can choose target.Artificial potential field method is mainly used for robot to plan path. Drawing on the repulsion potential field function principle of artificial potential field method, we introduce a repulsive force of robot to grid in the virtual market mechanism. Robots can be separated as far as possible, thus accelerating the process of exploration.The auction algorithm is the main method to coordinate robots in the virtual market. We find that most researchers focus their attention on bidding and determining the winner. In our auction algorithm, each robot gets one target in each auction circle, and then performs assigned target. The auction algorithm can be subdivided into waiting for all robot free algorithm(WA) and waiting for a robot free algorithm(WFA). Here we focus on two manners to determine the auction intervals. The first auction process starts from the moment when the current auction begins, and ends at the moment when all robots reach their targets; the second starts from the same moment, and ends at the moment whenever a robot finished its task. Then, the next auction begins. In the second case all robot except the one finished its task first give up their current tasks which are unfinished up to now. For the sake of simplicity, the corresponding algorithms are named as waiting for all robot free(WA) algorithm and waiting for a robot free(WFA) algorithm, respectively.Simulation experiments showed that two kinds of auction interval made significant difference in exploration time and auction times. For exploration time, the WFA is less than the WA, but in terms of auction times, the former is fewer than the latter. For walking distance, the WFA is further than the WA. We had also discussed in detail the differences between two different auction algorithms in different conditions. The simulation experiments confirmed that differences between them would perform differently in different situations.