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6 Sciences for Maneuver
Pages 89-104

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From page 89...
... These address certain issues that are less likely to be tackled by academic researchers -- issues such as development of world models and linking perception with cognition. Novel neural nets or perception algorithms, for instance, may help in a wide variety of tasks if they prove successful.
From page 90...
... These efforts are autonomous mobile information collection using value of information-enhanced belief approach, context-driven visual search in complex environments, air-ground team surveillance for complex three-dimensional (3D) environments,and unsupervised semantic scene labeling for streaming data.
From page 91...
... Deductive, Analogical, and Associative Reasoning in a Semantic Vector Space This work is performing deductive and analogical reasoning in a 300-dimension vector space, where the location in that space is decided by data mining in a large corpus. Words are then connected to other words throughout that high-dimension space.
From page 92...
... While this approach has sometimes been criticized as thwarting theoretical research, it is increasingly recognized for providing an often much needed "reality check." ARL owns and maintains a number of robotic platforms and, to the extent practicable, these need to be used to test and demonstrate new approaches and new proposed methods. Moreover, testing on real robots is likely to reveal practical challenges for which new theory is needed.
From page 93...
... Autonomous Mobile Information Collection Using a Value of Information-Enriched Belief Approach Injection of human knowledge can significantly increase the mathematical tractability of motion planning problems. As such, this research could investigate how this can systematically be done as mission is progressing (constraints permitting)
From page 94...
... Deductive, Analogical, and Associative Reasoning in a Semantic Vector Space The biggest question on this work is who else is doing related projects. There is certainly related work that is kept proprietary within Google and other companies; there is almost certainly relevant work within the federal government.
From page 95...
... Wingman Software Integration Laboratory The Wingman Software Integration Laboratory project integrates autonomous control and targeting of an unmanned high-mobility multipurpose wheeled vehicle weapon system with a manned vehicle, resulting in a human-machine combat team. The project's initial focus has been on the creation of an integrated simulation and testing environment that utilizes data from test locations in Michigan to generate realistic simulation and training situations for soldiers.
From page 96...
... The project has resulted in the creation of several technical reports; while there are no publications to date, it is not surprising, given the short period of this project. Data collection that is planned includes a simulation event at ARL to assess a warfighter machine interface for the roles in January-February 2018 and use of the Wingman System Integration Laboratory for training and human subjects' data collection during warfighter experimentation in June-August 2018.
From page 97...
... Leveraging Mutual Information to Enable Humans in the Loop This work would strongly benefit by using, to the extent possible, soldiers and intelligence analysts as human subjects. Subject matter experts (SMEs)
From page 98...
... The perception group's activities have focused around their fiscal year (FY) 2020 goal: "Semantic labeling of an increasingly larger vocabulary of objects and behaviors to permit a richer, more detailed description of the environment." Additional activities emphasize the practical aspects associated with ensuring correct spatial interpretation of sensory signals, so that the environmental descriptions are spatially accurate.
From page 99...
... One of these projects contributes a notable advance over the state of the art -- namely, an unsupervised method for learning action attributes from data and segmenting video sequences into action primitives, which serve as a compact signature for the activity. A topically related project integrates textual features during training to improve the performance of a deep learning-based activity recognizer.
From page 100...
... Three such research programs stand out -- research on low-ranked representation learning of action attributes (flexibility and extensibility) in focusing on human action attributes; research on autonomous mobile information collection using a value 100
From page 101...
... The research typically utilized an appropriate mix of theory and experimentation to arrive at well-reasoned conclusions. The Wingman Software Integration Laboratory was identified as a promising project potentially resulting in outstanding data and knowledge that could ultimately be transitioned to the field.
From page 102...
... This finding is supported by the fact that the only ARLTAB reviewed project that has used military personnel is the Toward Natural Dialogue with Robots: BOT Language project and this project will continue to recruit a mix of military personnel and civilians as human subjects in the future, as available. MHI project researchers could, to the extent possible, use soldiers, cadets, and realistic army operators.
From page 103...
... Centralized expertise would enable projects and experts to synergistically benefit each other, and shorten the learning curve for investigators who are using techniques closely related to other projects. Recommendation: ARL should centralize internal expertise on nontrivial tools and techniques, to shorten the learning curve and accelerate progress on related projects in perception.
From page 104...
... would help focus ARL's efforts and the efforts of individual researchers. The benchmarking effort is expected to enhance essential and foundational modeling, simulation, and theoretical components.


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