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Multi-Robot Interfaces and Operator Situational Awareness: Study of the Impact of Immersion and Prediction

机译:多机器人界面和操作员态势感知:沉浸和预测影响的研究

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摘要

Multi-robot missions are a challenge for operators in terms of workload and situational awareness. These operators have to receive data from the robots, extract information, understand the situation properly, make decisions, generate the adequate commands, and send them to the robots. The consequences of excessive workload and lack of awareness can vary from inefficiencies to accidents. This work focuses on the study of future operator interfaces of multi-robot systems, taking into account relevant issues such as multimodal interactions, immersive devices, predictive capabilities and adaptive displays. Specifically, four interfaces have been designed and developed: a conventional, a predictive conventional, a virtual reality and a predictive virtual reality interface. The four interfaces have been validated by the performance of twenty-four operators that supervised eight multi-robot missions of fire surveillance and extinguishing. The results of the workload and situational awareness tests show that virtual reality improves the situational awareness without increasing the workload of operators, whereas the effects of predictive components are not significant and depend on their implementation.
机译:就工作量和态势感知而言,多机器人任务对操作员而言是一项挑战。这些操作员必须从机器人接收数据,提取信息,正确了解情况,做出决定,生成适当的命令并将其发送给机器人。从低效率到事故,工作量过多和意识不足的后果可能会有所不同。这项工作着重研究未来的多机器人系统操作员界面,并考虑到相关问题,例如多模式交互,沉浸式设备,预测能力和自适应显示。具体地,已经设计和开发了四个界面:常规,预测性常规,虚拟现实和预测性虚拟现实界面。二十四个操作员的性能已经验证了这四个接口,该操作员监督了八个多机器人火灾监视和灭火任务。工作量和情境意识测试的结果表明,虚拟现实在不增加操作员工作量的情况下提高了情境意识,而预测组件的效果并不明显,取决于其实现。

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