Design of a guided missile operator assistant system for high-tempo intervention support

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Abstract

Controlling a short-range missile with in-flight reconfiguration capabilities places high demands on the design of the missile operators' control station and automated functions. To enable the missile operator to react fast, reliable and in a responsible manner to unforeseen events, e.g. high risk for collateral damage, an automated decision support system is investigated in this article. A common approach to reduce the high time demands of the operator is to transfer more functions from the human to the machine. Such emerging high levels of automation introduce ethical problems as well as new issues in human-automation-interaction to be resolved. At the Institute of Flight Systems we follow a well-established approach of human-automation cogency to assist human operators while keeping them fully involved in decision processes, i.e. "dual-mode cognitive automation, DMCA". This article presents first steps towards the application to a high-tempo mission with minimal information on the task and the tactical environment being available to the automated system. We present an approach to relieve the human from the time critical task to enter suchlike information into the system, thereby freeing cognitive resources for mission critical decisions. At the same time the assistant system observes the actions of the missile operator, infers his/her most likely intents, and adapts support functions accordingly. Comparing the human's control actions with intention related task models, the assistant system shall identify errors and suggest alternative actions or possible solutions. The operator remains in full control of all functions and decides whether to accept or decline the assistant systems advises. This article provides an overview over the main conceptual ideas and the current status of prototype implementation. © 2013 Springer-Verlag Berlin Heidelberg.

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APA

Kloss, T., & Schulte, A. (2013). Design of a guided missile operator assistant system for high-tempo intervention support. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8020 LNAI, pp. 273–281). Springer Verlag. https://doi.org/10.1007/978-3-642-39354-9_30

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