Self-localization for mobile robots by matching of two consecutive environmental range data

Abstract

While navigating, most autonomous mobile robots view things only in front of them and, as a result, they may collide with objects moving from the side or behind. To overcome this problem, an active omni-directional range sensor system is presented, that is capable of obtaining the omni-directional range data on a navigation environment through the use of a laser conic plane and a conic mirror. Based on this system configuration, we propose a self-localization algorithm. The proposed algorithm to estimate the current position and heading angle of mobile robots utilizes the registered range data obtained at two positions; current and previous and matches the two range informations. To show the effectiveness of the proposed algorithm, a series of simulations was conducted under various navigation conditions. The results show that the proposed algorithm is very efficient in processing, and can be effectively utilized for self-localization of mobile robots in unknown environments.