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Autonomous Surveillance Technologies Relating to Dismounted Soldiers

The development of the autonomous applications for dismounted Soldier systems is paramount to defeating our adversaries, such as China and Russia, in future combat. A comprehensive literature review is necessary to assist in defining the best path forward.

An overview of the type of situational awareness that exists for UAV surveillance. (Image: Army Research Laboratory)

The development of the artificial intelligence/machine learning (AI/ML) applications for dismounted Soldier systems is paramount to defeating our adversaries, such as China and Russia, in future combat. A comprehensive AI/ML literature review is a first step toward defining what exists and what can be applied and researched for our nation’s defense in future warfare. There is a clear need to use the latest AI/ML technologies in threat identification and elimination without U.S. lives lost. A comprehensive literature review is necessary to assist in defining the best path forward. In theory, networked unmanned aerial vehicles (UAVs) using onboard cameras may assist in successful navigation and threat identifications for ground troops. Furthermore, UAVs used as a surveillance and situational awareness (SA) tool may also be feasible to house weaponry to eliminate these threats.

As next-generation AI/ML-enabled optical systems, visual enhancement systems, and accessories are developed for use by the Army, a comprehensive examination of the human systems integration implications for networked use of these systems for teams of Soldiers/Operators is needed to examine human performance relative to teams equipped with legacy weapons and enablers.

The U.S. Army Combat Capabilities Development Command (DEVCOM) Analysis Center, known as DAC, Human Systems Integration Division proposed a comprehensive literature review of autonomous applications, AI, ML, and networked UAVs relative to use of dismounted Soldier systems (i.e., weapon systems and enablers), to include enabling swarmed unmanned aerial systems (UASs), as a conceptual documentation of the potential for autonomous systems during operational tasks. The primary search engines used were the ARL Online Library Catalog (WebCat) and Google Scholar.

To develop a networked UAV system to accurately identify and eliminate targets to dismounted Soldiers, the design of the HMI should be considered. HMI development considers human information processing and cognition and is necessary to optimize cognitive fightability. This is further dependent on how human senses are used to perceive the environment and how they may affect HMI modalities.

Models of information processing (human behavior classification, stimulus-central processing response, and effects of attention-sharing and multi-tasking), modalities of information (visual, auditory, and haptic), modalities of system control (the means by which the Soldier’s input or control commands into the system), and the analysis of Soldier needs (identify information needs and implement the best-suited modality) should be reviewed when implementing or designing HMI.

UAVs will play a vital role in the U.S. Army’s future force, providing visual feedback of the battlefield through the utilization of sensors, cameras, and munitions. An important factor for future building is the analysis of the balance of munitions, sensors, and fuel. UAV operators provide the eyes for the fight. The CL I and CL II UAVs provide battlefield signature patterns that keep the dismounted Soldiers alive.

To have successful wins, Soldiers must get inside the OODA by having a better SA than the threat by making quicker decisions and changing the situation in a way that is unobservable and incomprehensible by the opponent at a given time. AI can strengthen SA by identification of enemy presence, movement, identification, and mitigation.

UAVs can help improve SA with future advancements of data processing, fusion, and analytics. SA is paramount for dismounted Soldiers to engage efficiently. SA encompasses assessment (machine), awareness (user), and understanding (user– machine teaming). To address the multifaceted problem statement concerning UAVs, visual/optic systems, AI/ML, network teaming, and the use of legacy equipment, this literature review covers many interlocking factors. Among the numerous considerations are massive communications, high-level data traffic, low on-board energy storage, network configuration, different modalities to augment human cognition, speech, and audio, and UAV navigation, deployment optimization, and coordination.

This work was performed by Patricia M. Burcham for the Army Research Laboratory. For more information, download the Technical Support Package (free white paper) here  under the Vehicles and Robotics category. ARL-0113

Topics:
AR/AI Aerospace Aircraft Artificial Intelligence Artificial intelligence (AI) Autonomous vehicles Autonomy Defense Directed Energy Weapons, Detection, and Targeting Machine learning Military vehicles and equipment Munitions Platform Technology Threat Location, Targeting, & Surveillance Unmanned Air Vehicles/Systems (UAV/UAS) Unmanned aerial vehicles Vehicles
This Brief includes a Technical Support Package (TSP).
Document cover
A Comprehensive Literature Review of Autonomous Surveillance Technologies Relating to Dismounted Soldiers

(reference ARL-01132) is currently available for download from the TSP library.

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    Magazine cover
    Aerospace & Defense Technology Magazine

    This article first appeared in the May, 2023 issue of Aerospace & Defense Technology Magazine (Vol. 8 No. 3).

    Read more articles from this issue here.

    Read more articles from the archives here.

    Overview

    The document is a technical report titled "A Comprehensive Literature Review of Autonomous Surveillance Technologies Relating to Dismounted Soldiers," authored by Patricia M. Burcham and published in December 2022. It aims to explore and synthesize existing research on advanced surveillance technologies that can enhance the capabilities and safety of dismounted soldiers in military operations.

    The report highlights the importance of developing innovative ground-support technologies for surveillance, target identification, and target elimination. These advancements are crucial for improving soldiers' situational awareness (SA) and overall effectiveness in the field. The review emphasizes the need for research that addresses the challenges posed by modern warfare, including gray zone conflicts characterized by misinformation and disruptions to critical infrastructure.

    One of the key findings of the report is the effectiveness of graphical visualization in conveying complex information to operators. It notes that when dealing with large amounts of data, visual displays that integrate aerial and ground views can significantly enhance soldiers' battlefield awareness without increasing cognitive workload. This is particularly relevant in the context of using unmanned vehicles (UV) and other autonomous systems in surveillance operations.

    The report also discusses the advantages of incorporating speech and audio technologies to further support soldiers in the field. By leveraging these technologies, military personnel can receive real-time information and alerts, which can be critical for decision-making during operations.

    In conclusion, the report underscores the necessity for continued research and development in the area of autonomous surveillance technologies. It advocates for a focus on creating systems that not only improve operational efficiency but also enhance the safety and survival of dismounted soldiers in increasingly complex and dangerous environments.

    Overall, the document serves as a foundational resource for understanding the current landscape of autonomous surveillance technologies and their potential applications in military contexts, while also identifying gaps in research that need to be addressed to support future advancements.

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