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稿件标题: Mobile Robot Indoor Dual Kalman Filter Localization Based on Inertial Measurement and Stereo Vision
稿件作者: Lei Cheng *, Biao Song , Yating Dai , Huaiyu Wu , Yang Chen
关键字词: Mobile robot; Indoor localization; Inertial measurement; Stereo vision; dual Kalman filter
文章摘要: This paper presents a novel navigation method designed to support a real-time, efficient, accurate indoor localization for mobile robot system. It is applicable for inertial measurement units (IMU) consisting of gyroscopes, accelerometers, and magnetic besides stereo vision (SV). The current indoor mobile robot localization technology adopts traditional active sensing devices such as laser, and ultrasonic method which belongs to the signal of localization and navigation method which has low efficiency complex structure , and poor anti-interference ability. Through dual kalman filter (DKF) algorithm, the accumulated error of gyroscope can be reduced, while combining with stereo vision, mobile robot binocular stereo vision orientation of inertial location can be realized under the DKF mechanism. Dual DKF mechanism is introduced. First, high precision posture information of mobile robot can be obtained by using fusing kalman filter algorithm of accelerometer, gyroscope and magnetometer data. Secondly, inertial measurement precision can be optimized by using kalman filtering algorithm combined with machine vision localization algorithm. Results indicate that the method achieves the levels of accuracy location comparable to that of the IMU/SV fusion algorithm; < 0.0066 static RMS error, <0.0056 dynamic RMS error. The mobile robot using DKF algorithm of inertial navigation and stereo vision indoor localization is feasible.
收录刊物: 2017年2卷4期
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