可视化
工作量
战场
机器人
计算机科学
人机交互
形势意识
自动化
模拟
人工智能
工程类
操作系统
航空航天工程
机械工程
古代史
历史
作者
Judy Chen,Michael Barnes,Stephanie Quinn,William Plew
标识
DOI:10.1177/1071181311551312
摘要
RoboLeader is an intelligent agent that has the capabilities of coordinating a team of ground robots and revising route plans for the robots based on battlefield intelligence. Specifically, RoboLeader can support dynamic re-tasking based on battlefield developments as well as coordination between aerial and ground robots in pursuit of moving targets. In the current study, we manipulated the level of automation for RoboLeader as well as the presence of a visualization tool (which informed the participants about their target entrapment performance) in the RoboLeader user interface. Results showed that RoboLeader (Fully Automated condition) was more effective in encapsulating the moving targets than were the human operators (when they were either without assistance from RoboLeader or when they were partially assisted by RoboLeader). Participants successfully encapsulated the moving targets only 63% of the time in the Manual condition but 89% of the time when they were assisted by RoboLeader. Those participants who play video games frequently demonstrated significantly better encapsulation performance than did infrequent gamers; they also had better situation awareness of the mission environment. Visualization had little effect on participants’ performance. Finally, participants reported significantly higher workload when they were in the Manual condition than when they were assisted by RoboLeader.
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