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  March 29, 2019 | International, C4ISR, Other Defence

  DARPA: Using AI to Build Better Human-Machine Teams

  The inability of artificial intelligence (AI) to represent and model human partners is the single biggest challenge preventing effective human-machine teaming today. Current AI agents are able to respond to commands and follow through on instructions that are within their training, but are unable to understand intentions, expectations, emotions, and other aspects of social intelligence that are inherent to their human counterparts. This lack of understanding stymies efforts to create safe, efficient, and productive human-machine collaboration. “As humans, we are able to infer unobservable states, such as situational beliefs and goals, and use those to predict the subsequent actions, reactions, or needs of another individual,” said Dr. Joshua Elliott, a program manager in DARPA's Information Innovation Office (I2O). “Machines need to be able to do the same if we expect them to collaborate with us in a useful and effective way or serve as trusted members of a team.” Teaching machines social intelligence however is no small feat. Humans intuitively build mental models of the world around them that include approximations of the mental models of other humans – a skill called Theory of Mind (ToM). Humans use their ToM skill to infer the mental states of their teammates from observed actions and context, and are able to predict future actions based on those inferences. These models are built on each individual's existing sets of experiences, observations, and beliefs. Within a team setting, humans build shared mental models by aligning around key aspects of their environment, team, and strategies. ToM and shared mental models are key elements of human social intelligence that work together to enable effective human collaboration. DARPA's Artificial Social Intelligence for Successful Teams (ASIST) program seeks to develop foundational AI theory and systems that demonstrate the basic machine social skills necessary to facilitate effective machine-human collaboration. ASIST aims to create AI agents that demonstrate a Machine ToM, as well as the ability to participate effectively in a team by observing and understanding their environment and human partners, developing useful context-aware actions, and executing those actions at appropriate times. The agents developed under ASIST will need to operate across a number of scenarios, environments, and other variable circumstances, making the ability for them to evolve and adapt as needed critical. As such, ASIST will work to develop agents that can operate in increasingly complex environments, adapt to sudden change, and use observations to develop complex inferences and predictions. During the first phase of the program, ASIST plans to conduct experiments with single human-machine interactions to see how well the agents can infer human goals and situational awareness, using those insights to then predict their teammate's actions and provide useful recommended actions. As the program progresses, the complexity will increase with teams of up to 10 members interacting with the AI agents. During these experiments, ASIST will test the agents' ability to understand the cognitive model of the team – not just that of a single human – and use that understanding to develop appropriate situationally relevant actions. Full details on the program can be found in the Broad Agency Announcement (BAA) solicitation, which has been posted to the Federal Business Opportunities website, https://www.fbo.gov/index?s=opportunity&mode=form&id=9d4acf0aba98916288a541bd07810004&tab=core&_cview=1 https://www.darpa.mil/news-events/2019-03-21b

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  July 7, 2020 | International, Aerospace, Land

  Army on path to use space sensors to help guns on the ground see farther

  Jen Judson WASHINGTON — The Army is on a path to use space sensors to help its artillery see and shoot well beyond current capability. The service has already wrapped up an effort to achieve this capability, which took place in Europe in February and March, Gen. Mike Murray, Army Futures Command commander, told reporters in a media call. Murray was discussing how Army modernization would proceed despite COVID-19 social isolation measures in April. The Army will continue to build upon these early successes tapping into space assets to help guns on the ground hit long-range targets, an Army spokesperson told Defense News in a written statement. Conducted through Futures Command's cross functional team in charge of Assured Position, Navigation and Timing (A-PNT), the service was able to link space sensors with shooters in live-fire demonstrations in Grafenwoehr, Germany, on three separate occasions with the latest on March 23, the spokesperson wrote. Over the course of the demonstrations, the team “successfully sensed and hit targets at ranges beyond line of sight using satellite capabilities that have not been accessible to ground forces until now,” the spokesperson said. The exercise showed the “Army's ability to engage and defeat time sensitive targets with timely and accurate fires anywhere on the battlefield.” Tapping sensors that can help guide missiles and munitions to targets deep into the battlefield is critical to the Army's future long-range precision fires capability and key to operating across multiple domains. But achieving such distances requires connecting sensors and shooters that have never worked together before Long-Range Precision Fires (LRPF) is the Army's top modernization priority as it plays a critical role in the future battlefield and will be a centerpiece in the service's future Multi-Domain Operations doctrine currently in development. The LRPT cross functional team will continue to push the capabilities to far greater ranges than previously capable or than those distances previously allowed prior to the United States' withdrawal from the Intermediate-Range Nuclear Forces Treaty in 2019. During the initial live-fire demonstrations, a unit conducted an operation using the weapons and ammunition associated with their mission — in this case the Army integrated the capability with the Multiple Launch Rocket System (MLRS) and the M777 howitzer. The demonstrations used high explosive rounds equipped with a precision guidance kit fuze fired from the M777 howitzer or MRLS launcher. The Advanced Miniaturized Data Acquisition and Dissemination Vehicle accessed various sensors and target data was transmitted through the Joint Automated Deep Operations Coordination System and the Advanced Field Artillery Database System for the technical and tactical fire direction processes, the spokesperson detailed. The demonstrations gave “insight” into current capabilities “and their ability to link in novel ways to provide a capability down to the division operational level of combat,” the Army spokesperson said. Originally, pre-pandemic, the Army had planned to work on the capability throughout the scaled-back Defender Europe 2020 exercise using space-based sensors to pursue deep targets that “have not been responsive to ground forces until now,” according to the spokesperson. The APNT team will build upon the demonstrations by finding ways to reduce the sensor-to-shooter timeline to meet capability needs in the future anticipated operating environments. Ultimately, the Army will integrate the capability into the future Extended Range Cannon and a “full suite of Army fires platforms.” The ERCA cannon has already reached ranges of roughly 40 miles in recent tests at Yuma Proving Ground, Arizona. The service also plans to begin integrating with aviation platforms, the spokesperson said. The demonstrations are feeding into a “targeting process multi-domain operational strategy,” according to the spokesperson. The Army also plans to work on an architecture that connects both kinetic and non-kinetic assets from across joint, interagency and multinational partners. https://www.c4isrnet.com/2020/07/06/army-on-path-to-use-space-sensors-to-help-guns-on-the-ground-see-farther/

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  January 15, 2020 | International, Land

  Army Picks 2 Firms to Build Light and Medium Robotic Combat Vehicles

  By Matthew Cox The U.S. Army has announced that it plans to strike deals with QinetiQ North America and Textron Systems to build versions of the Robotic Combat Vehicle (RCV). Army Combat Capability Development Command's Ground Vehicle Systems Center, along with the service's Next-Generation Combat Vehicles cross-functional team, intend to award Other Transaction Agreements (OTA) to QinetiQ North America to build four light versions of the RCV and to Textron to build four medium versions, according to a recent news release from the National Advanced Mobility Consortium. The Army often uses OTAs under its new acquisition reform strategy, so it can have prototypes built quickly for experimenting with new designs. If all goes well in upcoming negotiations, the service intends to award the final OTAs for both variants by mid-February, the release states. The prototype RCVs will be used as part of the Army's "Robotic Campaign of Learning" in an effort to "determine the feasibility of integrating unmanned vehicles into ground combat operations," the release adds. The RCV effort is part of the Army's sweeping modernization effort, launched in 2017. The service wants to develop light, medium and heavy version of the RCV to give commanders the option of sending unmanned vehicles into combat against enemy forces. "Robots have the potential to revolutionize the way we conduct ground combat operations," Brig. Gen. Ross Coffman, director of the Next-Generation Combat Vehicle cross-functional team, said in the release. "Whether that's giving increased firepower to a dismounted patrol, breaching an enemy fighting position, or providing [chemical, biological, radiological, nuclear] reconnaissance, we envision these vehicles providing commanders more time and space for decisions and reducing risk to soldiers." Following final OTA notices, QinetiQ North America and Textron's RCVs will be used in a platoon level experiment in March and a company-level experiment in late 2021, the release states. The results of the experiments, along with the findings from several virtual experiments, will "inform a decision by the Army on how to proceed" with robotic combat vehicles in 2023, according to the release. Textron, along with its subsidiaries Howe and Howe Technologies and FLiR Systems Inc., displayed the Ripsaw M5 unmanned tracked vehicle as its RCV in October at the Association of the United States Army's annual meeting. QinetiQ North America teamed up with Pratt and Miller Defense to enter its Expeditionary Modular Autonomous Vehicle (EMAV) at AUSA as well. Jeffrey Langhout, director of the Ground Vehicle Systems Center, applauded the selection of QinetiQ North America and Textron as a "testament to the dedication and passion of the Army to giving our soldiers the best capabilities possible." "This is a great day for our Army, as we make another important step in learning how we can employ robotic vehicles into our future formations," he said in the release. https://www.military.com/daily-news/2020/01/14/army-picks-2-firms-build-light-and-medium-robotic-combat-vehicles.html