Infrastructure Monitoring With Multi-Robot Teams Gonc ¸alo Cabrita, Pedro Sousa, Lino Marques and An´ ıbal T. de Almeida Abstract— This article presents the first steps toward an automatic indoor environmental monitoring system through the use of a group of mobile robots. A metric map is provided a priori to the robots, ensuring the navigation, localization and extraction of points of interests for patrolling. The communica- tion layer is robust and allows any robot to enter or leave the patrolling task. The monitoring of the environment is achieved by acquiring environmental information during the patrolling. If an abnormal condition is detected, the system should react, providing a fine coverage of the suspicious area and an accurate identification of its source. Experiments were conducted inside a building and data was gathered and post processed. The yet preliminary results demonstrate the effectiveness of the method employed to control the system, showing good area coverage from the patrolling algorithm and acceptable representations of the collected variables (alcohol concentration and temperature). I. INTRODUCTION Environmental monitoring can be described as the process of collecting the necessary data to characterize the quality of the environment. This notion can be applied to countless indoor or outdoor applications. A wide range of Man-built structures accommodate chemicals potentially dangerous to both its occupants and Nature. Furthermore public buildings such as airports or train-stations have become preferential tar- gets for terrorist attacks. The timely detection of environmen- tal anomalies in this scenarios can prevent potential disasters and the consequent life losses and property damage [1]. Other structures might hold animal or plant life that needs certain environmental conditions in order to be properly sustained. Activities like agriculture can benefit from such technologies. In museums all over the world variables like temperature and humidity must be kept constant at all times in order to help preserve the art pieces which continuously struggle against time [2]. Environmental monitoring is usually achieved by means of a sensor network. The network nodes can be static, mobile or a combination of both. Static wireless sensor networks (WSN) consist of small nodes equipped with sensors capable of measuring the desired phenomena. The available solutions are usually cheap and easy to deploy, even over large areas, both indoors and outdoors. Static WSN have found their way into many monitoring applications, from museums [3] to large glaciers [4]. Mobile robots equipped with multiple sensors can create a mobile WSN. Mobile robot platforms come in many shapes, from small ground robots to unmanned G. Cabrita, P. Sousa, L. Marques and A. T. de Almeida are with Dept. of Electrical and Computer Engineering, Institute of Systems and Robotics, University of Coimbra, 3030-290 Coimbra, Portugal. {goncabrita, pvsousa, lino, adealmeida}@isr.uc.pt aerial vehicles (UAVs) or even underwater unmanned vehi- cles (UUVs), allowing for their deployment in almost any scenario. A mobile WSN will ultimately perform the same task a static WSN would, however a small number of mobile sensors is able to achieve a similar spatial resolution to that of a static WSN installed over a larger area. Furthermore a team of robots can be deployed virtually anywhere in a short amount of time, hence being a far more flexible solution [5]. Finally some applications can benefit from the use of both static and mobile WSNs. Mobile robots deployed within an environment equipped with a static WSN can tap into the existing network to access the environmental data of the covered area. This allows the robot to make decisions based on this data and get more detailed readings, thus improving the coverage and spatial resolution of the complete system [5]. Patrolling can be defined as the task of repeatedly visiting a desired location with the purpose of assessing certain aspects of its environmental state. Since it is not possible to cover all space at all times each point is visited once every T seconds, thus the frequency of patrolling is defined as 1/T Hz [6]. Also known as sweeping or repetitive coverage, the task of patrolling has had considerable attention from the mobile robot community in the past few years. Solutions for multi-robot scenarios usually approach the problem by dividing the area to patrol into sub-areas which are then assigned to the available robots. Once this is done each robot will patrol its own sub-area by means of a single- robot patrolling algorithm [6]. In 2002 Machado presented a discussion of multi-agent patrolling task issues. Several architectures were then compared, from which the best strategy was considered to be Conscientious Reactive, which is a local and reactive strategy with no communication, based on individual idleness and without central coordination [7]. Later in 2004, Chevaleyre carried out a study focused on two graph-theory centralized planning strategies: cyclic strate- gies and partitioning strategies [8]. Elmaliach studied the problem of generating patrolling paths for a team of robots and presented it in [6]. The patrolling algorithm presented guarantees that each point in the target area is covered at the same optimal frequency through the use of Hamilton cycles. More recently, Portugal and Rocha developed the Multilevel Subgraph Patrolling (MSP) algorithm [9]. This algorithm was proven to be superior to existing patrolling algorithms. Chemical variables can be monitored by a static sensor network or by mobile robots equipped with monitoring devices. The most common types of chemical variables monitored are: volatile organic compounds (VOCs), air con- taminants, and other type of toxic or hazardous gases [10],