Communication is crucial for human-robot collaborative tasks. In this context, legibility studies movement as the means of implicit communication between robotic systems and a human observer. This concept has been explored mostly for manipulators and humanoid robots. In contrast, little information is available in the literature about legibility of multi-robot systems or swarms, where simplicity and non-anthropomorphism of robots, along with the complexity of their interactions and aggregated behavior impose different challenges that are not encountered in single-robot scenarios. This article investigates legibility of multi-robot systems. Hence, we extend the definition of legibility, incorporating information about high-level goals in terms of the coordination objective of the group of robots, to previous results that focused solely on the legibility of spatial goals. A set of standard multi-robot algorithms corresponding to different coordination objectives are implemented and their legibility is evaluated in a user study, where participants observe the behavior of the multi-robot system in a virtual reality setup and are asked to identify the system’s spatial goal and coordination objective. The results of the study confirmed that coordination objectives are discernible by the users, hence multi-robot systems can be controlled to be legible, in terms of spatial goal and coordination objective.

The growing spread of robots for service and industrial purposes calls for versatile, intuitive and portable interaction approaches. In particular, in industrial environments, operators should be able to interact with robots in a fast, effective, and possibly effortless manner. To this end, reality enhancement techniques have been used to achieve efficient management and simplify interactions, in particular in manufacturing and logistics processes. Building upon this, in this paper we propose a system based on mixed reality that allows a ubiquitous interface for heterogeneous robotic systems in dynamic scenarios, where users are involved in different tasks and need to interact with different robots. By means of mixed reality, users can interact with a robot through manipulation of its virtual replica, which is always colocated with the user and is extracted when interaction is needed. The system has been tested in a simulated intralogistics setting, where different robots are present and require sporadic intervention by human operators, who are involved in other tasks. In our setting we consider the presence of drones and AGVs with different levels of autonomy, calling for different user interventions. The proposed approach has been validated in virtual reality, considering quantitative and qualitative assessment of performance and user's feedback.

This paper presents a coverage based control algorithm to coordinate a group of autonomous robots. Most of the solutions presented in the literature rely on an exact Voronoi partitioning, whose computation requires complete knowledge of the environment to be covered. This can be achieved only by robots with unlimited sensing capabilities, or through communication among robots in a limited sensing scenario. To overcome these limitations, we present a distributed control strategy to cover an unknown environment with a group of robots with limited sensing capabilities and in the absence of reliable communication. The control law is based on a limited Voronoi partitioning of the sensing area, and we demonstrate that the group of robots can optimally cover the environment using only information that is locally detected (without communication). The proposed method is validated by means of simulations and experiments carried out on a group of mobile robots.

Connectivity maintenance is crucial for the real world deployment of multi-robot systems, as it ultimately allows the robots to communicate, coordinate and perform tasks in a collaborative way. A connectivity maintenance controller must keep the multi-robot system connected independently from the system’s mission and in the presence of undesired real world effects such as communication delays, model errors, and computational time delays, among others. In this paper we present the implementation, on a real robotic setup, of a connectivity maintenance control strategy based on Control Barrier Functions. During experimentation, we found that the presence of communication delays has a significant impact on the performance of the controlled system, with respect to the ideal case. We propose a heuristic to counteract the effects of communication delays, and we verify its efficacy both in simulation and with physical robot experiments.

Connectivity maintenance is an essential aspect to consider while controlling a multi-robot system. In general, a multi-robot system should be connected to obtain a certain common objective. Connectivity must be kept regardless of the control strategy or the objective of the multi-robot system. Two main methods exist for connectivity maintenance: keep the initial connections (local connectivity) or allow modifications to the initial connections, but always keeping the overall system connected (global connectivity). In this paper we present a method that allows, at the same time, to maintain global connectivity and to implement the desired control strategy (e.g., consensus, formation control, coverage), all in an optimized fashion. For this purpose, we defined and implemented a Control Barrier Function that can incorporate constraints and objectives. We provide a mathematical proof of the method, and we demonstrate its versatility with simulations of different applications.

Multi-robot systems are able to achieve common objectives exchanging information among each other. This is possible exploiting a communication structure, usually modeled as a graph, whose topological properties (such as connectivity) are very relevant in the overall performance of the multirobot system. When considering mobile robots, such properties can change over time: robots are then controlled to preserve them, thus guaranteeing the possibility, for the overall system, to achieve its goals. This, however, implies limitations on the possible motion patterns of the robots, thus reducing the flexibility of the overall multi-robot system. In this paper we introduce teleoperation as a means to reduce these limitations, allowing temporary violations of topological properties, with the aim of increasing the flexibility of the multi-robot system.

Legibility can be defined as the ability of a robot to communicate its intent to the user. Legibility is relatively little investigated in multi-robot systems, but, in the literature, studies exist where the trajectory of manipulators is analyzed as a factor to improve the collaboration between robots and users. In this paper, we focus on the legibility of a group of mobile robots. To this end, we consider a set of motion-variables: trajectory, dispersion and stiffness. They are typical parameters that determine the motion of a group of robots. To analyze the effect of the motion-variables over legibility, Fisher's exact test and ANOVA (analysis of variance) were carried out. The data for the statistical analysis cover a full factorial plan and they were collected in a virtual reality set-up, where the users shared the environment with a group of robots. We investigate two aspects of legibility: the correctness and the rapidity of communication, namely if the communication happens correctly and how fast it happens. Trajectory was found to be relevant to correctly communicate the intention of the robots, while stiffness and dispersion were relevant for the rapidity of legibility.

Human-robot interaction has gained a lot of attention in recent years, since the use of robots can complement and improve human capabilities. To make such interaction smooth, proper interaction approaches are needed. Customarily these are tested in simplified scenarios and tame laboratory environment, since reproducing complex real use cases is often difficult. Achieved results are then not representative of actual interaction in reality and do not scale to complex scenarios. To overcome this issue, in this paper we consider the use of virtual reality as an alternative tool to assess HRI in those scenarios that are difficult to reproduce in reality. To this end, we compare the interaction experience for the same task, which is carried out in both virtual reality and real environment. To assess user's interaction in the two scenarios, we consider quantitative task related metrics, mental workload sustained, and subjective reporting. Results show that virtual reality allows to reproduce a faithful interaction experience and, thus, can be used to reliably validate human-robot interaction approaches in complex scenarios.