Abstract
A novel method of indoor mobile robot navigation is presented. The proposed approach fuses the data of odometry and electronic compass for navigation. It includes two calibration methods and a fusion algorithm. First of all, calibration method of systematic odometry error is used to reduce the error of navigation and provide the reliable estimate of pose of mobile robot for adaptive extended Kalman filter fusion algorithm later. Secondly, calibration method of electronic compass using an adaptive neural fuzzy inference system provides direction angle of mobile robot as observation for adaptive extended Kalman filter algorithm later. Finally, a fusion algorithm using adaptive extended Kalman filter algorithm fuses data of odometry and electronic compass that provides the position and orientation of mobile robot. In addition, the value of the parameter k of adaptive extended Kalman filter algorithm which is related to the process noise covariance is decided by fuzzy algorithm. In order to illustrate the feasibility of the proposed approach, two types of experiments are done: the first-type experiment is that the mobile robot runs along default path only with odometry, and the mobile robot with odometry and electronic compass in the second-type experiment utilizes the proposed approach for navigation. The results of experiments show that the error of localization and navigation in the first-type experiment is larger than one in the second-type experiment. They prove the good performance of the proposed approach.
Highlights
Navigation is a basic capability of mobile robotics that has to be solved,[1,2] which has always been an open and challenging problem in the past few decades.[3]
The value of the parameter k of adaptive extended Kalman filter (AEKF) algorithm which is related to the process noise covariance is decided by fuzzy algorithm
We have proposed an approach fusing the data of odometry and electronic compass to reduce the error of navigation and localization for mobile robot
Summary
Navigation is a basic capability of mobile robotics that has to be solved,[1,2] which has always been an open and challenging problem in the past few decades.[3]. The fundamental problem of electronic compass which is used in the indoor mobile robot localization and navigation is a deviation produced by external magnetic interference. A calibration method of electronic compass using ANFIS is used to solve the magnetic interference problem and provide direction angle as observation for AEKF algorithm later. The fusion of odometry and electronic compass using approach proposed in this article can calibrate the orientation error of mobile robot in real time to improve the accuracy of localization and navigation. The method detailed in “Calibration method of systematic odometry error” section is simple and easy to handle Another problem is that electronic compass mounted on indoor mobile robot suffers from magnetic interferences.
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