No 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.

This work presents an analysis of immersive realities and natural language applied to the teleoperation of hyper-redundant robots. Such devices have a large number of degrees of freedom, so they often exhibit complex configurations frustrating their spatial understanding. This work aims to contrast two hypotheses; first, if immersive interfaces enhance the telepresence and efficiency against conventional ones; and second, if natural language reduces workload and improves performance against other conventional tools. A total of 2 interfaces and 6 interaction tools have been tested by 50 people. As a result, immersive interfaces were more efficient, improved situational awareness and visual feedback, and were chosen by 94% of participants against conventional ones. On the other hand, participants performed better using natural language than conventional tools despite having less previous experience with the first ones. Additionally, according to 52% of the population, the preferred interaction tool was a mixed strategy that combined voice recognition and hand gestures. Therefore, it is concluded that immersive realities and natural language should play a very important role in the near future of hyper-redundant robots and their teleoperation.