Abstract: A two-step self-localization method for mobile robots based on laser information is proposed. After preprocessing the scanned data, the first step is to use the sequential search method to extract the straight lines in the indoor environment and establish the angle histogram, and then obtain the rotation angle of the robot by matching the angle histogram. The second step is to perform kernel density estimation on the laser data after angle matching, and establish the objective function with the translation vector as the parameter based on kernel correlation, and use the BFGS quasi-Newton method to solve the translation vector. Experimental results show that this method can effectively realize the precise self-localization of mobile robots. Keywords: mobile robot; self-localization; sequential search; histogram matching; kernel density correlation
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