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Implementation of Automation for Control of Robotic Systems

机译:机器人系统控制自动化的实现

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Future Combat Systems (FCS) represent an integrated materiel approach to transform the future U.S. Army into a more lethal, deployable, and survivable force. Technology alone will not ensure efficacy. Soldiers (and specifically their performance in this environment) will determine the success or failure of the fielded systems. In particular, robotic technology will be a vital component of future combat because it will extend manned capabilities, acting as force multipliers, and most importantly, it will save lives. The role of the human operator in the human-robot environment is not well understood; however, most contemplated systems will require active human control or supervision with the possibility of intervention. In the most extreme case, Soldiers will operate multiple systems while moving and while undergoing enemy fire. In all cases, workload and stress will be variable and unpredictable, changing rapidly as a function of the military environment. Automation technologies have been successfully applied to aid human operators in various environments, including aviation and military command and control. This report addresses strategies to minimize the demands on Soldiers in the robotic environment through the use of adaptive and adaptable automation. Adaptable interfaces allow the Soldier to define conditions for automation decisions during mission planning while adaptive interfaces automate tasks as a function of some environmental or behavioral indicator (Parasuraman, Sheridan, & Wickens, 2000). Although multiple robot control and the application of adaptive and adaptable automation have been investigated in some contexts, they have not been investigated as an aid to multiple robot control. We are examining the use of adaptive or adaptable automation to assist an operator who will control multiple robotic aerial and ground systems from a single interface in a vehicular environment. In this report, we provide an overview of the current state of the research.

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