A new approach is described for estimating the sensor configuration of a mobile robot, given a set of range data in a known environment. A robot is equipped with multi sensors. The environment is represented as a set of line segments in a xy plane. The perceptual equivalence classes of the sensor configuration space (x, y, ?) are precomputed. Two sensor configurations are considered equivalent of the mapping from the sensors to the visible line segments is identical. When a set of range data is observed at an execution time, a searching process is invoked in every equivalence class. Because the mapping of the sensors to obstacles is constant in a class, the objective function for maximum likelihood estimation behaves well. An Efficient algorithm to search for the minimum is presented. A simulation using randomly generated sensor data in randomly created robot environments is shown.