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This paper deals with the problem of guiding mobile sensors (or robots) to a phenomenon across a region covered by static sensors. We present a distributed, reliable and energy-efficient algorithm to construct a smoothed moving trajectory for a mobile robot. The reliable trajectory is realized by first constructing among static sensors a distributed hop count based artificial potential field (DH-APF) with only one local minimum near the phenomenon, and then navigating the robot to that minimum by an attractive force following the reversed gradient of the constructed field. Besides the attractive force towards the phenomenon, our algorithm adopts an additional repulsive force to push the robot away from obstacles, exploiting the fast sensing devices carried by the robot. Compared with previous navigation algorithms that guide the robot along a planned path, our algorithm can (1) tolerate the potential deviation from a planned path, since the DH-APF covers the entire deployment region; (2) mitigate the trajectory oscillation problem; (3) avoid the potential collision with obstacles; (4) save the precious energy of static sensors by configuring a large moving step size, which is not possible for algorithms neglecting the issue of navigation reliability. Our theoretical analysis of the above features considers practical sensor network issues including radio irregularity, packet loss and radio conflict. We implement the proposed algorithm over TinyOS and test its performance on the simulation platform with a high fidelity provided by TOSSIM and Tython. Simulation results verify the reliability and energy efficiency of the proposed mobile sensor navigation algorithm.