Research On Control Model Of Mobile Robot Based On Multi-Sensor Fusion

Intelligent is the inevitable development direction of the current mobile robot,and the important basis of intelligence is the sensor technology.With the continuous development of sensor technology,the information manifests itself more and more diverse,and the data collected by the sensor is also more and more The greater the complexity of the relationship between the information,information asymmetry increased,and the accuracy of information processing,timely,reliability requirements have greatly increased.This requires multi-sensor fusion technology,through computer technology to obtain the information from the multi-sensor processing,optimization to complete the judgment or system decision-making.In very many cases,it is often not enough to judge or perceive the external environment solely from the data collected by a single sensor.Multisensor data fusion technology effectively improves the accuracy,timing and reliability of data.With the development of multi-sensor data fusion technology,the technology has been successfully applied in many fields,including robotics,defense technology,industrial control,remote sensing monitoring,security protection and so on.Therefore,the research on multisensor data fusion technology is also of great significance.Mobile robots have been widely used in human life and production,reducing the workload of people,and multi-sensor fusion technology enhances the intelligent level of mobile robots.Therefore,based on the above purposes,this paper practices and verifies the relevant multi-sensor fusion algorithms by mobile robots.The main contents of this thesis are as follows:(1)To establish a mobile robot control system development environment and installation related to open development tools.(2)Set up the mobile robot control platform:Including the peripheral circuit and software design of the mobile robot.The software design includes the motor driver,the motor encoder pulse monitoring,ultrasonic ranging,touch sensors and other drivers and application programming.(3)The Kalman filter algorithm is used to improve the effect of mobile robot positioning,data fusion is made between the ultrasonic observation data and the estimated positioning data of the tachymeter and coder,and the localization of the fusion algorithm is verified by using Matlab.(4)Design fuzzy controller to achieve the target tracking of mobile robot,using the Matlab for fuzzy control position tracking verification.(5)Prove the feasibility of dead reckoning positioning based on the speed encoder by experimental verification and verify the feasibility of target tracking by fuzzy control of mobile robot.