Aiming at autonomous positioning of wheeled warehous robots, an indoor positioning method based on visual landmark and odometer data fusion was proposed. Firstly, by establishing a camera model, the rotation and translation relationship between the beacon and the camera was cleverly solved to obtain the positioning information. Then, based on the analysis of the characteristics of the angle difference between the gyroscope and the odometer, a method of angle fusion based on variance weight was proposed to deal with low update frequency and discontinuous positioning information problems. Finally, to compensate for a single sensor positioning defect, the odometer error model was designed to use a Kalman filter to integrate odometer and visual positioning information. The experiment was carried out on differential wheeled mobile robot. The results show that by using the proposed method the angle error and positioning error can be reduced obviously, and the positioning accuracy can be improved effectively. The repeat positioning error is less than 4 cm and the angle error is less than 2 degrees. This method is easy to operate and has strong practicability.

In order to deal with problem in private cloud environment caused by computing tasks with large amount of data, intensive computing and complex processing, an implementation of private cloud system based on dynamic service was proposed on the basis of public cloud computing and the characteristics of private cloud environment, which was able to adapt large-scale data processing. In this implementation, computing tasks were described by job files, processing workflows were constructed dynamically by job logic, service requests were driven by data streams and the large-scale data processing could be reflected more efficiently in MapReduce parallel framework. The experimental results show that this implementation offers a high practical value, can deal with computing tasks with large amount of data, intensive computing and complex processing correctly and efficiently.