Adaptive Source Localization by a Mobile Robot Using Signal Power Gradient in Sensor Networks

In this paper, we propose a novel approach of signal power gradient by which a robot adaptively searches a location-unknown sensor. While moving, the robot measures signal strength and estimates the direction of power gradient along which the robot moves in the next step. The correctness of estimated direction is analyzed and the probability of correct direction is obtained. Since the robot continuously measures signal strength while moving, it can effectively overcome the motion errors. Simulation results demonstrate that the robot can successfully reach the location-unknown sensor with probability close to one when the signal to noise ratio at the initial location is as low as 0 dB and the standard deviation of motion error is 10% step size.