A graph environment must be explored by a collection of mobile robots. Some of the robots, a priori unknown, may turn out to be unreliable. The graph is weighted and each node is assigned a deadline. The exploration is successful if each node of the graph is visited before its deadline by a reliable robot. The edge weight corresponds to the time needed by a robot to traverse the edge. Given the number of robots which may crash, is it possible to design an algorithm, which will always guarantee the exploration, independently of the choice of the subset of unreliable robots by the adversary? We find the optimal time, during which the graph may be explored. Our approach permits to find the maximal number of robots, which may turn out to be unreliable, and the graph is still guaranteed to be explored. We concentrate on line graphs and rings, for which we give positive results. We start with the case of the collections involving only reliable robots. We give algorithms finding optimal times needed for exploration when the robots are assigned to fixed initial positions as well as when such starting positions may be determined by the algorithm. We extend our consideration to the case when some number of robots may be unreliable. Our most surprising result is that solving the line exploration problem with robots at given positions, which may involve crash-faulty ones, is NP-hard. The same problem has polynomial solutions for a ring and for the case when the initial robots’ positions on the line are arbitrary. The exploration problem is shown to be NP-hard for star graphs, even when the team consists of only two reliable robots.

Additional Metadata
Keywords Deadline, Exploration, Fault, Graph, Line, NP-hard, Ring, Robot, Star graph
Persistent URL dx.doi.org/10.1007/978-3-319-73117-9_27
Series Lecture Notes in Computer Science
Czyzowicz, J. (Jurek), Godon, M. (Maxime), Kranakis, E, Labourel, A. (Arnaud), & Markou, E. (Euripides). (2018). Exploring graphs with time constraints by unreliable collections of mobile robots. In Lecture Notes in Computer Science. doi:10.1007/978-3-319-73117-9_27