An designated obstacle monitoring approach based on self-defined landmarks for a mobile robot

This paper proposes a new approach for a mobile robot to avoid obstacles based self-defined landmarks when it moves in the indoor environment. In this work, a 2D laser rangefinder is employed to detect the interior environment. The environmental maps, including global map and local map, are built by a series of feature extraction algorithms. Then, depending on self-defining landmarks, the mobile robot realizes its localization process through the feature association algorithm based on the optimal matching vertex. There are three factors that mainly influence the path selection process of the mobile robot: 1) the position information of the designated obstacle in the global map; 2) the external dimensions of the mobile robot; 3) the accuracy of the 2D laser rangefinder. To verify the effect of this proposed approach, an experiment has been done for the mobile robot to bypass a designated obstacle in the indoor environment. The experimental results show that the proposed approach is feasible to let the mobile robot bypass the designated obstacle along the selected path in the indoor environment, and the success rate is more than 80%.