Temporal Range Registration for Unmanned Ground and Aerial Vehicles

  • Authors:

  • R. Madhavan;T. Hong;E. Messina

  • Affiliations:

  • Intelligent Systems Division, National Institute of Standards and Technology, Gaithersburg, USA 20899-8230;Intelligent Systems Division, National Institute of Standards and Technology, Gaithersburg, USA 20899-8230;Intelligent Systems Division, National Institute of Standards and Technology, Gaithersburg, USA 20899-8230

  • Venue:
  • Journal of Intelligent and Robotic Systems
  • Year:
  • 2005

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Abstract

An iterative temporal registration algorithm is presented in this article for registering 3D range images obtained from unmanned ground and aerial vehicles traversing unstructured environments. We are primarily motivated by the development of 3D registration algorithms to overcome both the unavailability and unreliability of Global Positioning System (GPS) within required accuracy bounds for Unmanned Ground Vehicle (UGV) navigation. After suitable modifications to the well-known Iterative Closest Point (ICP) algorithm, the modified algorithm is shown to be robust to outliers and false matches during the registration of successive range images obtained from a scanning LAser Detection And Ranging (LADAR) rangefinder on the UGV. Towards registering LADAR images from the UGV with those from an Unmanned Aerial Vehicle (UAV) that flies over the terrain being traversed, we then propose a hybrid registration approach. In this approach to air to ground registration to estimate and update the position of the UGV, we register range data from two LADARs by combining a feature-based method with the aforementioned modified ICP algorithm. Registration of range data guarantees an estimate of the vehicle's position even when only one of the vehicles has GPS information. Temporal range registration enables position information to be continually maintained even when both vehicles can no longer maintain GPS contact. We present results of the registration algorithm in rugged terrain and urban environments using real field data acquired from two different LADARs on the UGV.