Abstract
In military settings, the maritime and expeditionary environments present unique operational, environmental, and logistical considerations for the human which are not present within land-based and established military locations (i.e. training or garrison settings). Advances in autonomous and unmanned systems may play key roles in addressing these issues. This paper will: briefly provide an overview of some human factors considerations in the maritime and expeditionary environment; address how autonomous systems may help overcome human factors challenges; and discuss how human-machine teaming and science & technology informed policy may be effective means to overcome some of autonomy’s unintended risks (i.e. accidental escalation) presented to military leaders and facilitate stability.
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Notes
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In 1995 for a brief time, Russia thought it might be under attack from the US, and Russian President Yeltsin opened his nuclear briefcase for the first time in history (other than as part of an exercise). These incidents highlight the vulnerability to human error present in MAD doctrine and its corollaries [6].
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Approximately 8,000 unmanned ground vehicles of various types have seen action in Iraq and Afghanistan. As of September 2010, unmanned ground vehicles have been used in over 125,000 missions, including suspected object identification and route clearance, to locate and defuse improvised explosive devices (IEDs). During these counter-IED missions, Army, Navy, and USMC explosive ordnance teams detected and defeated over 11,000 IEDs using UGVs. In 2009, US DoD completed almost 500,000 UAS flight hours just in support of operations in Afghanistan and Iraq. In May 2010, unmanned systems surpassed one million flight hours and in November 2010 achieved one million combat hours. The use of unmanned maritime system is not new. After World War II, unmanned surface vessels (USVs) conducted minesweeping missions and tested the radioactivity of water after atomic bomb tests. During the Vietnam War in an area south of Saigon, remotely controlled USVs conducted minesweeping operations [8].
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To be truly autonomous, a system must be able to compose independently and select among various courses of action to accomplish goals based on its knowledge and understanding of the environment, itself, and the situation [4]. From an engineering perspective, building true autonomy is a series of technological challenges akin to developing understanding of and then building a human-being from scratch.
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One example of a rapidly emerging area for autonomous systems to benefit the military is the mine countermeasures (MCM) domain. Current manned and unmanned MCM platforms all require personnel in the minefield. MCM-1 class ships can detect, classify, and neutralize all known types of mines, but require large manned crews. Increased utilization of autonomy-enabled UUVs can significantly reduce personnel risk during MCM operations. Personnel can conduct MCM operations remotely rather than entering the minefield. The UUV program has demonstrated significant progress in utilizing UUVs for MCM. Further gains are possible. Development of both autonomy in motion and autonomy at rest will reduce tactical timelines with intensive operator involvement. Increased autonomy in the areas of automated target recognition and mine disposal could reduce risk and decrease the tactical timeline [4].
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Another example is the Anti-Submarine Warfare (ASW) Continuous Trail Unmanned Vessel (ACTUV). This is an unmanned vessel optimized to track quiet diesel electric submarines at a fraction of their size and cost. This system will be able independently deploy on missions spanning thousands of kilometers of range and months of endurance under a sparse remote supervisory control model. This includes autonomous compliance with maritime laws and conventions for safe navigation, autonomous system management for operational reliability, and autonomous interactions with an intelligent adversary. While the ACTUV program is focused on demonstrating the ASW tracking capability in this configuration, the core platform and autonomy technologies will be broadly extendable to a wide range of missions and configurations for future unmanned naval vessels [13, 14].
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In contrast to the U.S., China, South Korea, Japan, and India are investing heavily in higher education and research. India and China are systematically luring back their scientists and engineers after they are trained in the U.S. This contrast in investment is evident in the specific areas related to robotics and manufacturing. Korea has been investing $100M per year for 10 years (2002–2012) into robotics research and education as part of their 21st Century Frontier Program. European Commission investments total over $1.5 billion into robotics and cognitive systems, and manufacturing. Japan is investing $350M over the next 10 years in humanoid robotics, service robotics, and intelligent environments. In 2016, Japan has also announced a major push to become leader in robotics with a 5 year investment of $1B for industrial robotics. The non-defense U.S. federal investment in robotics and automation is small by most measures compared to these investments [12].
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The strategic corporal concept was coined in 1999 by USMC General Charles Krulak but popularized during OEF/OIF and refers to the concept that low-level operational personnel must be capable of not just thinking through immediate tactical situations, but must also be capable of anticipating the operational and strategic consequences.
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Approved for public release: distribution unlimited. The contents of this paper reflect the personal views of the author and are not necessarily endorsed by the SPAWAR Systems Center Pacific, Department of the Navy, or the US Government. The author would like to thank Gregory Lafave for feedback on an earlier version of this manuscript.
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Norris, J.N. (2018). Human Factors in Military Maritime and Expeditionary Settings: Opportunity for Autonomous Systems?. In: Chen, J. (eds) Advances in Human Factors in Robots and Unmanned Systems. AHFE 2017. Advances in Intelligent Systems and Computing, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-60384-1_14
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