IRobot Self-localization Using EKF
Shuqiang Zhao; Jason Gu; Yongsheng Ou; Wei Zhang
2016
会议名称IEEE International Conference on Information and Automation(ICIA)
会议地点中国宁波
英文摘要Self-Localization plays an important role in the mobile robot autonomous navigation. The Wheel Mobile robot usually contains a large number of different sensors, such as odometry, gyro, laser, camera and so on. All these sensors provide the information of robot localization and all these information should be considered for the optimal location. However, for the cost of the iRobot, we could not be equipped with a lot of sensors. We have only encoder sensor and gyro sensor. So this paper researches mobile robot localization only using odometer and gyro sensor based on Extended Kalman Filter (EKF). The method is that the iRobot fuses the messages from encoder sensor and gyro sensor by EKF theory, which can collect the errors that obtained the robot’s orientation and position. The experiment results appear that the proposed self-localization method is effective and feasible.
收录类别EI
语种英语
内容类型会议论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/10144]  
专题深圳先进技术研究院_集成所
作者单位2016
推荐引用方式
GB/T 7714
Shuqiang Zhao,Jason Gu,Yongsheng Ou,et al. IRobot Self-localization Using EKF[C]. 见:IEEE International Conference on Information and Automation(ICIA). 中国宁波.
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