Tactical situational awareness in unstructured and mixed indoor / outdoor scenarios is needed for urban combat as well as rescue operations. Two of the key functionalities needed by robot systems to function in an unknown environment are the ability to build a map of the environment and to determine its position within that map. In this paper, we present a strategy to build dense maps and to automatically close loops from 3D point clouds; this has been integrated into a mapping system dubbed OmniMapper. We will present both the underlying system, and experimental results from a variety of environments such as office buildings, at military training facilities and in large scale mixed indoor and outdoor environments.
Autonomous systems operating in militarily-relevant environments are valuable assets due to the increased situational
awareness they provide to the Warfighter. To further advance the current state of these systems, a collaborative
experiment was conducted as part of the Safe Operations of Unmanned Systems for Reconnaissance in Complex
Environments (SOURCE) Army Technology Objective (ATO). We present the findings from this large-scale experiment
which spanned several research areas, including 3D mapping and exploration, communications maintenance, and visual
For 3D mapping and exploration, we evaluated loop closure using Iterative Closest Point (ICP). To improve current
communications systems, the limitations of an existing mesh network were analyzed. Also, camera data from a
Microsoft Kinect was used to test autonomous stairway detection and modeling algorithms. This paper will detail the
experiment procedure and the preliminary results for each of these tests.
Currently fielded small unmanned ground vehicles (SUGVs) are operated via teleoperation. This method of operation
requires a high level of operator involvement within, or near within, line of sight of the robot. As advances are made in
autonomy algorithms, capabilities such as automated mapping can be developed to allow SUGVs to be used to provide
situational awareness with an increased standoff distance while simultaneously reducing operator involvement.
In order to realize these goals, it is paramount the data produced by the robot is not only accurate, but also presented in
an intuitive manner to the robot operator. The focus of this paper is how to effectively present map data produced by a
SUGV in order to drive the design of a future user interface. The effectiveness of several 2D and 3D mapping
capabilities was evaluated by presenting a collection of pre-recorded data sets of a SUGV mapping a building in an
urban environment to a user panel of Soldiers. The data sets were presented to each Soldier in several different formats
to evaluate multiple factors, including update frequency and presentation style. Once all of the data sets were presented,
a survey was administered. The questions in the survey were designed to gauge the overall usefulness of the mapping
algorithm presentations as an information generating tool. This paper presents the development of this test protocol
along with the results of the survey.