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

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 has been presented, that is capable of obtaining the omni-directional range data on 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 head 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.