Research On The Navigation And Position Method Of Mowing Robot Based On GPS And Digital Box And Needle

The robot has widely applied in the fields of industry, agriculture and military affairs.The mowing robot in this paper used electric pedrail robot as a research platform for the first time, and the electric pedrail robot has the advantage of the landform applicability and all-weather that other robot has not. This choise has created a new method in the research of the mowing robot.One of the most important research problems on the mowing robot is how to carry out the aim at navigation and position. At present, most of robots use the sensor of vision or the sensor of sound to obtain the navigation information. Other mowing robots use the current transducer to obtain the information of its work area from the cable that laied at work area beforehand. In this paper, we headmostly apply the GPS and GPS/DR navigation technic in the mowing robot and establish the GPS Kalman filter model and GPS/DR adaptive Kalman filter model. These models have good effect by test.First,this paper introduced the research on GPS error, we aim at examing the error of GPS is the colour noise or not.We collected position data on a stationary site by using AgGPS 132 receiver. By using the methods of numerical analysis and system identification, the Arma model [AR(1)] of GPS error was establishedin GPS Kalman filter,the GPS error is treated as Gauss white noise commonly.But we use the GPS error model which established to improve the GPS Kalman filter and establish the GPS Kalman filter model in the condition that GPS error is colour noise. After experiment testing,the GPS Kalman filter model has inproved position precision greatly than GPS.In order to validate that the GPS dynamic navigation error is diversity in different direction, we use the AgGPS 132 receiver in dynamic navigation in direction of east -west and north-south,then we proved that the error of GPS's dynamic navigation in different direction is distinguishing.This result has directive significance in robot's route plan.We use the GPS receiver, the digital box and needle and the distance information calculating from robot's PWM assembled the GPS/DR navigation system and establish the GPS/DR adaptive Kalman filter model.The GPS/DR adaptive Kalman filter model has improved position precision more by experiment testing.Finally, this paper analyzed the source of position error and compare the results of examination among four navigation method, that is the GPS dynamic position method,GPS Kalman filter method,DR method and GPS/DR adaptive Kalman filter,and give some advice in mending.The GPS Kalman filter model and the GPS/DR adaptive Kalman filter model in this paper improve the position precision greatly and they are worth of application in robot navigation and position.