Abstract
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.
Highlights
Multi-robot missions have experienced a noticeable growth over the last decades
A quick analysis of the means show that immersive interfaces are better than their conventional counterparts in terms of workload and situational awareness, whereas the effects of the predictive components depend on the interface and the variable
This order points out the virtual reality interfaces tend to increase the situational awareness of operators, whereas the effects of the predictive components depend on the interface
Summary
Multi-robot missions have experienced a noticeable growth over the last decades. Their performance has been improved significantly, and their range of application has been extended. These missions are applied in multiple domains (air, ground and sea) for diverse purposes (surveillance, search and rescue, environmental monitoring...). According to [1], the most relevant problems in scenarios with multiple robots and single operator are peaks of workload and lack of situational awareness. According to [2], the use of robots in urban search and rescue scenarios has a bottleneck in situational awareness, which can be addressed by considering the robots as sources of information and fusing this information properly
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