A Complete Exploration and Mapping Algorithm for Robots in Unknown Obstacle-Cluttered Environments

This paper considers the problem of exploring an unknown, obstacle-cluttered, bounded environment and constructing a complete topological map using a robot equipped with range sensors. We propose an exploration and mapping algorithm for this problem utilizing a target obstacle selection rule and a sector selection rule. This algorithm aids the robot in making decisions to expand the explored area based on information obtained at each intersection, ultimately constructing a complete topological map within finite time. We demonstrate that this algorithm guarantees provable mapping completeness and provides an upper bound on mapping time in standard map environments. Compared to a previous complete map construction algorithm, our approach accelerates the exploration of unknown areas and reduces the number of revisits, thus im-proving exploration efficiency. Simulation experiments in various environments validate the completeness and efficiency of our algorithm.