An efficient strategy integrating grid and topological information for robot exploration

Efficiency is an important issue to robot's autonomous exploration of unknown environments, which is the focus of this paper. When exploring, usually, a robot evaluates the candidate observation points according to a utility function, and the point that maximizes this utility function is selected. This paper advances a grid-topological utility function for decision making of the next observation point. Our strategy whose core is this utility function can be used in the exploration executed by single robot system or multi-robot system. A new path-planning algorithm: cost overflow, is also proposed, which enables our strategy run online. Experiment with real robot system and simulation results show that our strategy is efficient in both time and energy.