Abstract The Canadian Traveler Problem (CTP) is a navigation problem where a graph is initially known, but some edges may be blocked with a known probability. The task is to minimize travel effort of reaching the goal. We generalize CTP to allow for remote sensing actions, now requiring minimization of the sum of the travel cost and the remote sensing cost. Finding optimal policies for both versions is intractable. We provide optimal solutions for special case graphs. We then develop a framework that utilizes heuristics to determine when and where to sense the environment in order to minimize total costs. Several such heuristics, based on the expected total cost are introduced. Empirical evaluations show the benefifits of our heuristics and support some of the theoretical results