The subject of this article is a scheme for distributed outdoor localization of a team of robots and the use of the robot team for outdoor terrain mapping. Localization is accomplished via Extended Kalman Filtering (EKF). In the distributed EKF-based scheme for localization, heterogeneity of the available sensors is exploited in the absence or degradation of absolute sensors aboard the team members. The terrain mapping technique then utilizes localization information to facilitate the fusion of vision-based range information of environmental features with changes in elevation profile across the terrain. The result is a terrain matrix from which a metric map is then generated. The proposed algorithms are implemented using field data obtained from a team of robots traversing an uneven outdoor terrain.
Raj Madhavan, Kingsley Fregene, Lynne E. Parker