Most work on navigation minimize travel effort or computational effort of the navigating agent, while assuming that unknown components of the environment are sensed by the agent at no cost. We introduce a framework for navigation where the agent needs to minimize a global cost function which includes both the travel cost and the sensing cost. At each point in time, the agent needs to decide whether to perform sense queries or to move towards the target. We develop the SN (Sensing-based Navigation) framework that utilizes heuristic functions to determine when and where to sense the environment in order to minimize total costs. We develop several such heuristics, based on the expected total cost. Experimental results show the benefits of our heuristics over existing work, and demonstrate the generality of the SN framework.