Swarm robotics: a review from the swarm engineering perspective <s> Human-swarm interaction <s> In a variety of emergency settings robot assistance has been identified as highly valuable, providing remote, and thus safe, access and operation. There are many different forms of human-robot interactions, allowing a team of humans and robots to take advantage of skills of each team member. A relatively new area of research considers interactions between human and a team of robots performing as a swarm. This work is concerned with the interactive use of autonomous robots in fire emergency settings. In particular, we consider a swarm of robots that are capable of supporting and enhancing fire fighting operations co-operatively and we investigate how firefighters in the field work with such a swarm. This paper outlines some of the key characteristics of this emergency setting. It discusses possible forms of interactions with swarm robotics being examined in the GUARDIANS project. The paper addresses the use of assistive swarm robotics to support firefighters with navigation and search operations. It reports on existing firefighters operations and how human-swarm interactions are to be used during such operations. The design approaches for human-swarm interaction are described and the preliminary work in the area are outlined. The paper ends by linking current expertise with common features of emergency related interaction design. <s> BIB001 </s> Swarm robotics: a review from the swarm engineering perspective <s> Human-swarm interaction <s> The purpose of the demonstrator is to present a novel system for gesture-based interaction between humans and a swarm of mobile robots. The human interacts with the swarm by showing hand gestures using an orange glove. Following initial hand glove detection, the robots move to adapt their positions and viewpoints. The purpose is to improve individual sensing performance and maximize the gesture information mutually gathered by the swarm as a whole. Using multi-hop message relaying, robots spread their opinions and the associated confidence about the issued hand gesture throughout the swarm. To let the robots in the swarm integrate and weight the different opinions, we developed a distributed consensus protocol. When a robot has gathered enough evidence, it takes a decision for the hand gesture, and sends it into the swarm. Different decisions compete with each other. The one assessed with the highest confidence eventually wins. When consensus is reached about the hand gesture, the swarm acts accordingly, for example by moving to a location, or splitting into groups. The working of the system is shown and explained in the video accessible at the following address:http://www.idsia.ch/ gianni/SwarmRobotics/aamasdemo.zip. <s> BIB002 </s> Swarm robotics: a review from the swarm engineering perspective <s> Human-swarm interaction <s> In this paper we investigate principles of swarm control that enable a human operator to exert influence on and control large swarms of robots. We present two principles, coined selection and beacon control, that differ with respect to their temporal and spatial persistence. The former requires active selection of groups of robots while the latter exerts a passive influence on nearby robots. Both principles are implemented in a testbed in which operators exert influence on a robot swarm by switching between a set of behaviors ranging from trivial behaviors up to distributed autonomous algorithms. Performance is tested in a series of complex foraging tasks in environments with different obstacles ranging from open to cluttered and structured. The robotic swarm has only local communication and sensing capabilities with the number of robots ranging from 50 to 200. Experiments with human operators utilizing either selection or beacon control are compared with each other and to a simple autonomous swarm with regard to performance, adaptation to complex environments, and scalability to larger swarms. Our results show superior performance of autonomous swarms in open environments, of selection control in complex environments, and indicate a potential for scaling beacon control to larger swarms. <s> BIB003
Swarm robotics systems are conceived to be autonomous and to make decisions in a distributed way. While these are in general considered to be positive features, they also limit the degree of control of a human operator over the system. In fact, since there is neither a leader nor centralized control, the operator does not have a simple way to control the behavior of the system. Human-swarm interaction studies how a human operator can control a swarm and receive feedback information from it. McLurkin et al. (2006) developed a simple mechanism in which robots are able to provide information to human operators using LEDs and sound. BIB001 proposed an analysis of different possible approaches to humanswarm interaction, classifying them in direct human-swarm interaction, direct swarmhuman interaction, and remote interaction via base station.  used a Microsoft Kinect system to give commands through gestures to a swarm of robots. The human operator is able to command the swarm to select, split, merge, and rotate. BIB002 used a similar approach based on gestures. The robots observe the gestures of a human operator. Each robot is able to guess the performed gesture, but due to its limited vision capabilities, different robots could make a different guess. To reach consensus, the robots vote using multi-hop communication and finally execute the order associated with the performed gesture. BIB003 presented two approaches to control a swarm. The first approach is based on global communication: a human operator uses a central computer to select and control a subgroup of robots. The second approach is based on local interactions: the human operator places pre-programmed beacons in the environment. Such beacons are used to communicate a new behavior to the robots which are in their communication range.