They are potentially useful for other pipeline networks for the delivery of oil, water, sewage, chemicals and so on. In the long run, they are also applicable to other physically enclosed harsh environments, such as water tanks, wings of air vehicles, mines and even outer space [7,8].In this paper we utilize the combination of an integral approach and an object-oriented hierarchical structure. either Although there are existing works combining ideas from robotic swarms, artificial intelligence and object-oriented design, the work presented in this paper distinguishes itself by a new research context of natural gas pipeline inspection tasks and a novel integration of the related ideas in the above fields in the same framework of mobile sensor networks.The rest of the paper is organized as follows.

The formulation of the problem and the proposed general solution framework is presented in Section 2. In Section 3, we present a simulated study on how to design algorithms for mobile sensors to learn to adapt Inhibitors,Modulators,Libraries to an unknown environment and benefit from collaborating with its peers. A robotic experimental study for coordinating mobile sensors to maneuver as a team with local information is then discussed in Section 4. We make concluding remarks at the end of the paper.2.?Problem Formulation and Proposed Integral Approach2.1. Problem FormulationWe consider a team of sensor equipped autonomous robots [9] that operate in a given natural gas pipeline network. Each robot is powered by batteries Inhibitors,Modulators,Libraries and can move freely inside the pipeline network.

It can detect within its sensing range a predefined fault on the wall of a tube and then record it in its memory. The information about the detected fault, together with other related sensing data, can be processed by the computational Inhibitors,Modulators,Libraries unit of the robot for further usage. The raw data and the processed information can be communicated between robots when they are within communication ranges of one another. Each robot has a distinguishable identity in the group, which is used to initiate or plan a coordinated action among a subset of the group members. The gas pipeline network environment is assumed to be stationary, i.e., no significant changes of its condition happen while the robots are doing the inspection job. However, the robots have no prior knowledge about the working condition of the pipeline network.

In other words, the robots have to rely on their sensing, computation and communication Inhibitors,Modulators,Libraries capabilities to build up their knowledge about the environment that they are Cilengitide working in.The problem to be studied is how to control and coordinate the robots�� sensing, computation enzalutamide mechanism of action and communication activities so that the robots can cover the given pipeline network with the highest possible accuracy and the shortest possible execution time. Here, the definition for accuracy and execution time may vary for different networks and different robots at hand.