Landmark-Based Particle Localization Algorithm for Mobile Robots With a Fish-Eye Vision System

Abstract

Localization is a crucial ability for autonomous robots and landmark-based localization can be effectively used because it enables localization with only landmark information. For localization, the omnidirectional vision system is efficiently used for robots to obtain information of the surrounding environment, but it is expensive and has some distortion. In this sense, the fish-eye lens vision system can be an alternative. Compared to the omnidirectional vision system, however, it obtains less landmark information at a time so that it needs a localization algorithm using less landmark information. To solve this problem, this paper proposes a novel landmark-based particle localization algorithm for the global localization problem called relocation. It can localize the pose of the robot using only two landmarks. In this algorithm, information on bearing angle and distance of landmarks is used to calculate a possible area of the location of the robot and then particles, each of which represents a pose of the robot, are randomly distributed in the calculated area. The pose of the robot is identified by selecting a particle with the highest importance weight among the distributed particles. Computer simulations and experiments demonstrate the effectiveness of the proposed algorithm.