Mapping and localization module in a mobile robot for insulating building crawl spaces

This paper presents a novel robotic system that applies spray foam insulation in underfloor voids in order to improve the energy efficiency of buildings. The work focuses on solving the mapping and localization problems in such environments, since they are a key factor in the autonomy of the robot. Solving these tasks in underfloor voids is especially challenging because the terrain is extremely uneven due to the presence of stones, bricks and sand. Within these environments, the robot should be able to localize itself and apply the insulation foam to the underside of the floor. The robot is equipped with a 2D laser sensor which permits building point clouds from several positions of the underfloor environment. The localization process is solved by estimating the position of the robot with respect to previously known positions. For this purpose, the alignment between point clouds is calculated. This paper describes two algorithms to robustly obtain the alignment between two positions. The proposed algorithms are tested with a set of point clouds captured with a laser scan in several environments under real working conditions. The results show that the localization problem can be solved in such challenging underfloor voids by using depth information.