Implementation of a Long-Distance Navigation Method of Low Cost Structure That Combines a Localization Using Magnetic Information and a Lateral Position Compensation

摘要

We have proposed a navigation method using magnetic information that occurs in the environment. This paper proposes a improve navigation method that combines a localization using magnetic information and a lateral error compensation based on external geometric information. In our previous method, it is required to adjust parameters used for the robot navigation. This adjustment is needed excluding unreliable magnetic information. On the other hand, our proposed method enables a robot to travel long distance without adjustment parameters even if the unreliable magnetic information is included. The robot is able to identify its position with the particle filter on a topological map using magnetic information. Furthermore, the robot uses external geometric information for only compensate the lateral error. As a result, the localization accuracy is increased and is not depend on geometric information. In addition, these methods are applicable to the robot using simple algorithm, computational and memory costs are low. Through the navigation experiments, we show that the robot achieved over 2 km navigation in real world. Moreover, the proposed method is compared to other two methods. Finally, the usefulness and advantage of the proposed method are presented.