Emergencies in industrial warehouses are a major concern for fire fighters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus the robot swarm is able to provide guidance information to the humans. Together with the fire fighters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings.keywords: Swarm robotics, search and rescue, human robot (swarm) interface, mobile ad-hoc networks.

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Abstract. PurposeThe GUARDIANS multi-robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots guide and accompany the firefighters on site whilst indicating possible obstacles and the locations of danger and maintaining communications links. Design/methodology/approach In order to fulfill the aforementioned tasks the robots need to exhibit certain behaviours. Among the basic behaviours are capabilities to stay together as a group, that is, generate a formation and navigate while keeping this formation. The control model used to generate these behaviours is based on the so-called social potential field framework, which we adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots. Findings The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus the application has forced us to redefine the concept of a formation. Using the graph-theoretic terminology, we can say that a formation may be stretched out as a path or be compact as a star or wheel. We have implemented the developed behaviours in simulation environments as well as on real ERA-MOBI robots commonly referred to as Erratics. We discuss advantages and shortcomings of our model, based on the simulations as well as on the implementation with a team of Erratics. Originality/value This paper discusses the concept of a robot formation in the context of a real world application of a robot team (swarm).

A theoretical framework for generating navigation the squad robust to failures of individual robots and its size behaviour patterns in mixed human-robot groups in complex envi-may vary considerably. ronments is proposed. This framework represents an essential part inThe basic behaviours that we cover in the mixed humanthe development of a multiple robot-human system for assisting fire-robot team are: robot, fire-fighter and obstacle avoidfighters in search and rescue operations in the GUARDIANS project. robottram and robon keepig. In obstacle the In order to produce the desired behaviours an artificial potential ance/attraction and formation keeping. In order to achieve the field method has been developed. We distinguish a three classes of listed behaviours, we use the social potential field framework, agents: robots, humans and obstacles, and apply different potential introduced by Reif and Wang [2], for developing our model. functions to them. Depending on the situation, we switch from one Each robot observes its environment including the other robots, function to another; this allows to generate desired behaviour patterns . . a as well as to avoid certain local minima. Typical behaviour patterns thcfreinghte Angdiostcesn maketal fnations decsion are singled out and their stability is discussed. Stability analysis accordingly. Applying different potential functions depending is based on geometric considerations, that permits to avoid bulky on whether a robot, the fire-fighter or an obstacle is detected computations and provide graphic demonstrations of convergence. we can generate a global behaviour that keeps the group of The proposed framework can be used in other robotic applications robots around the fire-fighter. The social potential field method where a group of heterogenous agents is deployed, allows the group of autonomous mobile robots to follow the Mixed human-robot team artificial potential fields, multi-moving human while avoiding other robots and the obstacles robot formations, navigation patterns at the same time.The simulation results and theoretical considerations indi-I. INTRODUCTION cate that our algorithm is robust and flexible to robot teamsThe mixed human-robot team in the GUARDIANS project' of different sizes as well as to failures of individual robots, consists of several autonomous mobile robots to assist fire-making it suitable to formation generation and navigation fighters in search and rescue operations in an industrial maintenance in dynamic environments. The inherent complexwarehouse in the event or danger of fire [19]. Among the ity of the emerging behaviours makes hard to fully predict the possible tasks that robots should be able to perform are collective behaviour on the basis of the behaviours of each the following: searching and exploring the warehouse and individual robot. However, we are able to single out several gathering information; maintaining the communication link typical emerging behaviour patterns. We conclude the paper to the outside base station and supporting ...

Abstract-Search and rescue operations are often undertaken in smoke filled and noisy environments in which rescue teams must rely on haptic feedback for navigation and safe exit. In this paper, we discuss designing and evaluating a haptic interface to enable a human being to follow a robot through an environment with no-visibility. We first discuss the considerations that have led to our current interface design. The second part of the paper describes our testing procedure and the results of our first tests. Based on these results we discuss future improvements of our design.Keywords -human robot interaction; haptic interface; support for no-visibility/visually impaired

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Abstract-This paper presents salient features of humanhuman interaction where one person with limited auditory and visual perception of the environment (a follower) is guided by an agent with full perceptual capabilities (a guider) via a hard rein along a given path. We investigate several salient features of the interaction between the guider and the follower such as a) the order of an autoregressive control policy that maps states of the follower to actions of the guider, b) how the guider may modulate the pulling force in response to the confidence level of the follower, and c) how learning may successively apportion the responsibility of control across different muscles of the guider. Based on experimental systems identification on human demonstrations from ten pairs of naive subjects, we show that guiders tend to adopt a 3 rd order auto-regressive predictive control policy and followers tend to adopt 2 nd order reactive control policy. Moreover, the extracted guider's control policy was implemented and validated by human-robot interaction experiments. By modeling the follower's dynamics with a time varying virtual damped inertial system, we found that it is the coefficient of virtual damping which is most sensitive to the confidence level of the follower. We used these experimental insights to derive a novel controller that integrates an optimal order control policy with a push/pull force modulator in response to the confidence level of the follower monitored using a time varying virtual damped inertial model.Index Terms-Human robot interaction, hard rein, haptic communication, predictive and reactive control policies.

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