Survey on Coverage Path Planning with Unmanned Aerial Vehicles <s> Real-Time Search Methods <s> An algorithm which solves the coverage and search problems in either explored or unexplored terrains is described. The coverage problem requires that the robot pass over all parts of the terrain that are free of obstacles. The search problem requires that the robot seek a specified target in a given terrain. The target need not be present in the terrain; in that case, the algorithm will realize the fact after a thorough search. In an explored terrain problem, a model of the terrain is available indicating which regions of the terrain are traversable. In an unexplored terrain problem, such a model is not available, thus forcing the robot to build the model by the use of sensors. It is proved that the algorithm guarantees complete coverage and a thorough search if physically possible. Due to its use of indirect control, the algorithm is not complicated and is thus simple to implement. > <s> BIB001 </s> Survey on Coverage Path Planning with Unmanned Aerial Vehicles <s> Real-Time Search Methods <s> Although researchers have studied which factors influence the behavior of traditional search algorithms, currently not much is known about how domain properties influence the performance of real-time search algorithms. In this paper we demonstrate, both theoretically and experimentally, that Eulerian state spaces (a superset of undirected state spaces) are very easy for some existing real-time search algorithms to solve: even real-time search algorithms that can be intractable, in general, are efficient for Eulerian state spaces. Because traditional real-time search testbeds (such as the eight puzzle and gridworlds) are Eulerian, they cannot be used to distinguish between efficient and inefficient real-time search algorithms. It follows that one has to use non-Eulerian domains to demonstrate the general superiority of a given algorithm. To this end, we present two classes of hard-to-search state spaces and demonstrate the performance of various real-time search algorithms on them. <s> BIB002 </s> Survey on Coverage Path Planning with Unmanned Aerial Vehicles <s> Real-Time Search Methods <s> This paper presents ETHNOS-IV - a real-time programming environment for the design of a system composed of different robots, devices and external supervising or control stations. ETHNOS is being used for different service robotics applications and it is has also been used successfully used in RoboCup in the Italian ART robot team during the Stockholm '99 competition. It provides support from three main point of views which will be addressed in detail: inter-robot and intra-robot communication, real-time task scheduling, and software engineering, platform independence and code-reuse. Experimental results will also be presented. <s> BIB003 </s> Survey on Coverage Path Planning with Unmanned Aerial Vehicles <s> Real-Time Search Methods <s> This paper describes an algorithm, which has been specifically designed to solve the problem of multirobot-controlled frequency coverage (MRCFC), in which a team of robots are requested to repeatedly visit a set of predefined locations of the environment according to a specified frequency distribution. The algorithm has low requirements in terms of computational power, does not require inter-robot communication, and can even be implemented on memoryless robots. Moreover, it has proven to be statistically complete as well as easily implementable on real, marketable robot swarms for real-world applications. <s> BIB004
A performance of real-time multi-robot coverage algorithms is analyzed by Nattero et al.  . The authors explore classical heuristics, such as Edge Counting BIB002 , PatrolPGRAPH* BIB004 , Node Counting BIB001 , and Leaning Real-Time A*  . The algorithms were evaluated in simulations with land robots in terms of the required coverage time and, implicitly, the energy required to perform a mission. Four types of experiments were executed varying aspects, such as grid size, grid topology, quantity of robots and required visits. The Node Counting overcomes the other solutions during the simulations and it was implemented in a real system with a quadcopter and a hexacopter. An off-board control implemented using Robot Operating System (ROS)  is applied to guide vehicles sending target positions and periodically receiving the localization information of the vehicles. Control dynamics and vehicles localization are executed on-board through ETHNOS framework BIB003 . The decision process is centralized in the off-board station, which communicates with the vehicles using an ROS/ETHNOS interface. To apply virtual pheromones in an aerial scope, a centralized process is required, which makes the system less robust to failures once all vehicles depend on the communication with the ground control station to perform their tasks.