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Robotics Program Advances Large Platform Autonomy in Urban Battleground

By Dariusz Mikulski

The U.S. Army is introducing advanced military ground robotics systems into theatre in order to minimize the number of warfighters placed in harm’s way for certain dangerous missions. Some of Soldiers’ most difficult and dangerous missions involve complex urban environments, where an enemy has the advantage of knowing the layout of a city and ability to blend in with the crowds.

The SOURCE ATO uses sensors placed over large UGVs to autonomously navigate terrains. The technology developed through this program could play an important role in advancing vehicle autonomy to keep warfighters safe. (U.S. Army image.) The SOURCE ATO uses sensors placed over large UGVs to autonomously navigate terrains. The technology developed through this program could play an important role in advancing vehicle autonomy to keep warfighters safe. (U.S. Army image.)

Robotic assets can level the playing field for these types of missions, giving warfighters the ability to patrol an urban area without exposing themselves to attacks. But autonomous technologies on these robotic platforms must also ensure the safety of pedestrians and property during such missions.

As such, U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) is leading an effort to incorporate a high degree of safety into autonomous technologies through the Safe Operations of Unmanned Systems for Reconnaissance in Complex Environments Advanced Technology Objective (SOURCE ATO). The SOURCE ATO represents the integration of cutting-edge technology and algorithms for safe autonomy of large robotic platforms.

Preparing Vehicles for the Urban Theater

Through SOURCE ATO, the Army is advancing Unmanned Ground Vehicle (UGV) technology development specifically for Military Operations in Urban Terrain (MOUT) environments. MOUT sites and missions contain complex and technically challenging variables for UGV operation, such as close operation with warfighters and vehicles, and potential interaction with civilians and enemy combatants. Often, the environmental surroundings are geometrically and visually complex and may include man-made, structured elements— such as buildings — or natural, unstructured elements — such as culverts and caves. Maneuverability may also be constrained in close-quarter operation.

The payoff for solving the autonomy challenge in MOUT missions is safe large-UGV operation in proximity to warfighters, pedestrians, and vehicles. Increased vehicle autonomy may reduce warfighters’ mental strain by offloading much of the supervisory burden to the robotic platform, allowing for better mission focus and situational awareness.

Testing and Evaluation

The SOURCE ATO uses sensors placed over large UGVs to autonomously navigate terrains. The technology developed through this program could play an important role in advancing vehicle autonomy to keep warfighters safe. (U.S. Army image.) The SOURCE ATO uses sensors placed over large UGVs to autonomously navigate terrains. The technology developed through this program could play an important role in advancing vehicle autonomy to keep warfighters safe. (U.S. Army image.)

The SOURCE ATO will execute its final round of experiments in September and October 2012 at Camp Lejeune, NC, and conclude with a joint demonstration event with the Improved Mobility and Operational Performance through Autonomous Technologies (IMOPAT) ATO program. The Capstone experiment will evaluate the performance differences between the advanced Autonomous Navigation System (ANS) and an alternative low-cost commercial off-the-shelf (COTS) system on two large vehicle platforms. In addition, for the first time, the SOURCE ATO will officially test the Dismount System, a new technological capability to follow a dismounted warfighter rather than a waypoint plan. This system consists of human-mounted pedometers, localization, and operator control unit (OCU), interfacing along with vehicle-based computer vision technologies for human tracking.

To date, the SOURCE program has successfully completed two prior field experiments: the Baseline experiment in January-February 2011 and the Enhanced experiment in November 2011. In both experiments, engineers recorded a large amount of data, including logged sensor data, resulting vehicle behavior, logged internal software data, independent ground truth data for moving and static obstacles, and test personnel observations and comments. The Baseline experiment included basic autonomous Move-On-Route operation on a road network as well as initial moving obstacle avoidance using the off-road behaviors. The Enhanced experiment demonstrated key autonomous operation capabilities in a complex urban MOUT site, such as Move-On-Route, Tele-operation, and remote situational awareness.

The SOURCE ATO, and the data gathered from it, will have lasting effects on future Army autonomous technology development programs. For instance, the Occupant Centric Protection (OCP) Technology Enabled Capability Demonstration (TECD) team plans to leverage the results as it develops driver’s aids and situational awareness (SA) technologies. The program is anticipated to help support the Lighten-The-Load (LTL) TECD, which focuses on leader-follower, waypoint following, and dismounted following capabilities. Additionally, the SOURCE ATO results can feed the development of new autonomous mobility capabilities, simulation environments (such as MODSIM), and sensor systems operational data in the Autonomous Mobility Appliqué System (AMAS) program. AMAS will integrate and demonstrate a modular, scalable COTS-based sensor package for navigation, safety and driver’s assist on a variety of UGV platforms in three as-yet undefined mission scenarios.

Preliminary results from the final SOURCE ATO experiment will be published later this year. For more information about this and other TARDEC robotic programs, keep checking back on this site for more information.

Author Bio:

Dariusz Mikulski is a TARDEC Robotics Research Engineer. He is a Ph.D. candidate in Electrical and Computer Engineering at Oakland University in Rochester, MI, and serves as the Technical Lead in the TARDEC SOURCE ATO program. His current research interests include computational trust with a focus on improving robot team decision making for military applications in unstructured, uncertain and hostile environments.