Mobile Robot Localization Using Differential Evolution

This paper presents a new localization method using differential evolution (DE) algorithm in a mobile robot localization problem. Mobile robot localization is one of important problems in many mobile robot systems. Some stochastic approaches (e.g. Kalman Filter, Particle Filter, etc.) are the dominant methods on this research community. Applications of evolutionary computations (ECs) for the mobile robot localization are very rare. Hence, this paper considers the new localization method using DE for mobile robot’s position tracking. In some fundamental experiments using raw data, the efficacy of the proposed localization method is shown.