## 2 Related Work  
The CERNATRO human-robot interface allows an inexperienced user to easily operate a set of different modular robots, which is usually adapted to the intervention request. However, it did not allow for synchronisation between the different agents, making particular tasks difficult, including a high level of coordination. The topic of controlling multiple robots during remote intervention has been studied in detail in the past few years. The problem has often been addressed under a different perspective, with the objective of optimising the number of robots and the number of operators during an intervention. The goal is to maximise the overall intervention performance and to ensure human, environmental, and robot safety at any time. Several factors cooperate in the resulting task performance: human factors such as mental workload, stress, and errors must be taken into account, in particular when the tasks are difficult and safety critical; robot factors comprise the level of autonomy of the robot, the communication, and the sensors and tools available. It has been demonstrated that, in determined scenarios, such as in urban search and rescue, the use of a single operator controlling one robot often resulted in missed opportunities for a more efficient  
Figure 4: Common technological aspects of cooperative interventions in radioactive and underwater environments. task execution or in key details being left out. In the urban search and rescue scenario, it has been shown that an intervention supervisor collaborating with the robotic operator greatly improves the overall task efficiency [9]. Studies showed how additional robotic roles to task experts affect operators' multitasking and efficiency [10; 11; 12]. In certain scenarios, a single operator is in charge of controlling multiple robots, although in most cases, the operator must accomplish a single task using several robots, where there is a context switch cost coming from the transition between multiple parallel tasks [13]. Designing an HRI that enables a single nonexpert user to control a coordinated team of robots is a challenging objective [14], especially when the task requires accurate synchronisation between mobile manipulators [15]. Also, the presence of communication constraints, as found in underground tunnels and underwater scenarios, makes the problem even more complex. In fact, enabling human supervision of the robot team facilitates the introduction of many teamwork applications, in particular in those scenarios where an expert of the application is necessary, where the expert has more knowledge of the tools and targets to intervene on rather than the robots to be controlled. This finds an important application at CERN as well as in marine archaeology [16]. Increasing the level of autonomy of the agents [17] ensures the operator's ability to multi-tasking, resulting in increased efficiency and task safety. It has been demonstrated that an operator can control multiple agents, provided that they exhibit an appropriate level of autonomy [18; 19]. In this context, the _fun-out_ measure represents the number of independent and heterogeneous robots that an operator can control simultaneously [20]. Some experiments provide a user interface to enable a team of operators to control a heterogeneous team of robots [21]. This is especially important when sharing control with the robot team can be done on time as well as in task assignment. However, this finds limitations when a task has to be performed by two robots in a synchronised manner, especially for grasping interventions. Other works focus on human-robot cooperation not only at a distance but also on the field. For this reason, it is important to find a way to share their internal knowledge (e.g., ontologies) of the application as well as the goal of the cooperative mission [22]. Although the topic of multi-agent collaboration is investigated in more and more detail, little studies provided accurate performance metrics to set a baseline for future improvements.