Sonar based Simultaneous Localization and Mapping using a Neuro Evolutionary Optimization

This paper addresses a solution of simultaneous localization and mapping (SLAM) using a neuro evolutionary optimization algorithm. The proposed algorithm solves the global optimization problem of the SLAM using the cost function which represents the quality of a robot´s trajectory in a world coordinate frame. In our algorithm, the neural network helps to estimate the difference of two consecutive positions accurately using the sensor inputs at each position. The evolutionary programming (EP) is used to find the most suitable neural network. The proposed neural network based SLAM is applied to the robot which has sonar sensors. The various experimental results demonstrate that the neural network based SLAM guarantees a consistent environmental map under the sonar sensor measurements.