A graph search algorithm for indoor pursuit/evasion

Using concepts from both robotics and graph theory, we formulate the problem of indoor pursuit/evasion in terms of searching the nodes of a graph for a mobile evader. We present the IGNS (Iterative Greedy Node Search) algorithm, which performs offline guaranteed search (i.e. no matter how the evader moves, it will eventually be captured). Furthermore, the algorithm produces an internal search (the searchers move only along the edges of the graph; “teleporting” is not used) and exploits non-monotonicity, extended visibility and finite evader speed to reduce the number of searchers required to clear an environment. We present search experiments for several indoor environments, in all of which the algorithm succeeds in clearing the graph (i.e. capturing the evader).