Abstract
Positioning is the basic link in a multi-mobile robot control system, and is also a problem that must be solved before completing a specified task. The positioning method can be generally divided into relative positioning and absolute positioning. Absolute positioning method refers to that the robot calculates its current position by acquiring the reference information of some known positions in the outside world, calculating the relationship between itself and the reference information. Absolute positioning generally adopts methods based on beacons, environment map matching, and visual positioning. The relative positioning method mainly uses the inertial navigation system INS. The inertial navigation system directly fixes the inertial measurement unit composed of the gyroscope and the accelerometer to the target device, and uses the inertial devices such as the gyroscope and the accelerometer to measure the triaxial angular velocity and The three-axis acceleration information is measured and integrated, and the mobile robot coordinates are updated in real time. Combined with the initial inertial information of the target device, navigation information such as the attitude, speed, and position of the target device is obtained through integral operation [1-2]. The inertial navigation system does not depend on external information when it is working, and is not easily damaged by interference. As an autonomous navigation system, it has the advantages of high data update rate and high short-term positioning accuracy [3]. However, under the long-term operation of inertial navigation, due to the cumulative error of integration, the positioning accuracy is seriously degraded, so it is necessary to seek an external positioning method to correct its position information [4]
Highlights
In order to solve the problem of inertial navigation under long-term operation due to the cumulative error of integration, the positioning accuracy is reduced and GPS absolute positioning cannot be used
This paper proposes a WSN / INS combined positioning algorithm combined with wireless sensor network positioning technology
The WSN / INS navigation method uses the sensor data of INS and WSN, and calculates the redundant or complementary information of these data in space or time through the Kalman filter according to the specified method to obtain unified and consistent positioning information
Summary
In order to solve the problem of inertial navigation under long-term operation due to the cumulative error of integration, the positioning accuracy is reduced and GPS absolute positioning cannot be used. The WSN / INS navigation method uses the sensor data of INS and WSN, and calculates the redundant or complementary information of these data in space or time through the Kalman filter according to the specified method to obtain unified and consistent positioning information. Because the data collected by multi-sensor nodes is redundant and complementary, it can expand the observation scale in time and space, and strengthen the credibility of effective data. This is more robust and effective for mobile robot formation systems in dynamic environments. The research work in this chapter will provide a theoretical basis for the subsequent navigation and formation control research
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
