| With the fast development of new technology in intelligent control, computer science, networking, bionics and artificial intelligence, mobile robot has become the focus in the field of robotics and automation. Autonomous localization is an essential task for intelligence mobile robot navigation, and multi-sensor collaborating technology can provide much more information to realize Autonomous localization. The dissertation is mainly focus on robotic localization algorithm in a known environment and multi-sensor data fusion. Here is the brief work:Firstly, the techniques of robot localization are introduced. And then this paper gives the summarize of the research significance and the state of the research at home and abroad. In plus, the related issues of Multi-sensor information fusion algorithm are discussed, including: the basic principles and the research content.Secondly, the mobile robot kinematics model is build. The principle and error model of two commonly use robot sensor are analyzed. Several common data fusion algorithms are analyzed and the environment representation methods in robotics are also compared. The extended Kalman filter algorithm is focused on.Finally, this chapter mainly researches on the algorithm and the implement of robot localization based on multi-sensor information fusion algorithm with Kalman filter method. Then, an improvement is make to the algorithm after researching on the measurement variance of system. The experiments demonstrate the algorithm can gain good results for localization. |
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