Abstract
This chapter introduces the increase in mobile robot positioning based on the global positioning system (GPS) using data from other sensors. Positioning using the GPS is determined, at any time, by measuring the time delay in a radio signal broadcast from several satellites, and using this and the speed of propagation to calculate the distance to the satellites. The position on earth is then calculated by triangulation of intersecting radio signals at the GPS receiver. Using the GPS for positioning is subject to several sources of errors: ionosphere and troposphere delays, signal multi-path, number of visible satellites, satellite geometry/shading, and so on. A typical civilian GPS receiver provides 6 to 12 meters accuracy, depending on the number of satellites available. This accuracy can be reduced to 1 m by using a differential GPS (DGPS) which employs a second receiver at a fixed location to compute corrections to the GPS satellite measurements. In order to increase the accuracy of the robot positioning, we use an extended Kalman Filter (EKF) to integrate data from the DGPS with data from an inertial navigation system (INS) and robot encoders. This will also allow kipping robot positioning even if no satellite is visible.
Original language | English |
---|---|
Title of host publication | Using Robots in Hazardous Environments |
Subtitle of host publication | Landmine Detection, De-Mining and Other Applications |
Publisher | Woodhead Publishing Limited |
Pages | 269-282 |
Number of pages | 14 |
ISBN (Print) | 9781845697860 |
DOIs | |
Publication status | Published - 20 Dec 2010 |
Keywords
- Data fusion
- Global positioning system
- Inertial navigation system
- Kalman filter
- Localization
- Sensors