Improvement of Map Building during the Exploration of Polygonal Environments using the Range Data

In this paper we consider problem of exploration and mapping of unknown polygonal environments. To construct a map of unknown environment we first must have exploration algorithm, and we have to choose a map representation method. Unknown environment needed to be explored is an indoor office environment. We use line map representation method since it is easy to represent office environment using line segments and it is significantly less memory consuming than occupancy grid map representation method. We combined two algorithms for line map building: 1) weighted line fitting algorithm developed by Pfister et al. [9], which incorporates noise models of the range sensor and robot’s pose uncertainty and 2) exploration algorithm developed by Ekman et al. [2], which explores polygonal environments using ideal range data with no uncertainty and dealing with no positional uncertainty. We combined and improved both methods to derive complete exploration of polygonal environments and statistically sound mapping solution. The algorithms were tested using Pioneer 3DX mobile robot equipped with a laser range finder.