초록 ▼

A horizontal navigation system aided by a carrier phase differential Global Positioning System (GPS) receiver and a Laser-Scanner (LS) for an Autonomous Ground Vehicle (AGV). The high accuracy vehicle navigation system is highly demanded for advanced AGVs. Although high positioning accuracy is achie

A horizontal navigation system aided by a carrier phase differential Global Positioning System (GPS) receiver and a Laser-Scanner (LS) for an Autonomous Ground Vehicle (AGV). The high accuracy vehicle navigation system is highly demanded for advanced AGVs. Although high positioning accuracy is achievable by a high performance RTK-GPS receiver, the performance should be considerably degraded in a high-blockage environment due to tall buildings and other obstacles. The present navigation system is to provide decimeter-level positioning accuracy in such a severe environment for precise GPS positioning. The horizontal navigation system is composed of a low cost Fiber Optic Gyro (FOG) and a precise odometer. The navigation errors are estimated using a tightly coupled Extended Kalman Filter (EKF). The measurements of the EKF are double differenced code and carrier phase from a dual frequency GPS receiver and relative positions derived from laser scanner measurements.

대표청구항 ▼

The invention claimed is: 1. A navigational method of determining a position and heading of an object, comprising: calculating the position and the heading of the object based on an output of a velocity detecting device and an output of a yaw rate detecting device; estimating, based on a carrier ph

The invention claimed is: 1. A navigational method of determining a position and heading of an object, comprising: calculating the position and the heading of the object based on an output of a velocity detecting device and an output of a yaw rate detecting device; estimating, based on a carrier phase and a pseudorange received from a global positioning satellite, (1) an error of the velocity detecting device, (2) an error of the yaw rate detecting device, (3) a position error and a heading error of the object, and (4) an integer-valued bias of a carrier, wherein the estimating step includes estimating a relative range and/or a relative angle between a known landmark and the object based on an angle measured by an angle measuring device provided on the object and stored position data of the known landmark; and calculating an observation error based on the estimated relative range; and updating the position and the heading of the object based on the estimated position error and the estimated heading error. 2. The method of claim 1, wherein the estimating step comprises: estimating the relative range based on geometrical data of at least two known landmarks and a known yaw angle of the angle measuring device. 3. The method of claim 1, wherein the estimating step comprises: estimating the relative range based on the angle measured by a laser scanner. 4. The method of claim 1, wherein the calculating step comprises: calculating the position and the heading of the object using the dynamical equations: wherein N, E, and D are components of the position, Φ is the heading, V is a velocity measured by the velocity detecting device, r is a yaw rate measured by the yaw rate detecting device, t is time, and b is a predetermined distance. 5. The method of claim 1, wherein the estimating step comprises: estimating a float ambiguity vector of double-differenced carrier phase using an extended Kalman filter; and resolving ambiguity in the integer-valued bias of the carrier, using a Lambda method, based on the estimated float ambiguity vector of double-differenced carrier phase estimated by the extended Kalman filter. 6. The method of claim 1, wherein the calculating step comprises: calculating the position and the heading of the object based on outputs of an odometer and a rate gyro. 7. The method of claim 1, wherein the landmark is one of a traffic sign, a curbstone, and a white line. 8. The method of claim 1, wherein the angle measuring device is an image sensor. 9. A navigational system for determining a position and heading of an object comprising: a navigation calculation device configured to calculate the position and the heading of the object based on an output of a velocity detecting device and an output of a yaw rate detecting device; and an estimator configured to estimate, based on a carrier phase and a pseudorange received from a global positioning satellite, (1) an error of the velocity detecting device, (2) an error of the yaw rate detecting device, (3) a position error and a heading error of the object, and (4) an integer-valued bias of a carrier, wherein the estimator is configured to estimate a relative range and/or a relative angle between a known landmark and the object based on an angle measured by an angle measuring device provided on the object and stored position data of the known landmark, wherein the navigation calculation device is configured to update the position and the heading of the object based on the position error and the heading error estimated by the estimator. 10. The navigational system of claim 9, wherein the estimator is configured to calculate an observation error based on the estimated relative range. 11. The navigational system of claim 9, wherein the estimator is configured to estimate the relative range based on geometrical data of at least two known landmarks and a known yaw angle of the angle measuring device. 12. The navigational system of claim 9, wherein the navigation calculation device is configured to calculate the position and the heading of the vehicle using the dynamical equations: wherein N, E, and D are components of the position, φ is the heading, V is a velocity measured by the velocity detecting device, r is a yaw rate measured by the yaw rate detecting device, t is time, and b is a predetermined distance. 13. The navigational system of claim 9, wherein the estimator comprises: an extended Kalman filter configured to estimate a float ambiguity vector of double-differenced carrier phase; and an ambiguity resolution device configured to resolve ambiguity in the integer-valued bias of the carrier, using a Lambda method, based on the float ambiguity vector of double-differenced carrier phase estimated by the extended Kalman filter. 14. The navigational system of claim 9, wherein the estimator is configured to estimate the relative range between one of a traffic sign, a curbstone, and a white line, and the vehicle. 15. The navigational system of claim 9, wherein the angle measuring device is an image sensor. 16. A vehicle, comprising: a propulsion system configured to propel the vehicle; and a navigational system for determining a position and heading of the vehicle using inertial and satellite navigation, the navigational system including: a velocity detecting device configured to detect a velocity of the vehicle; a yaw rate detecting device configured to detect a yaw rate of the vehicle; a landmark database configured to store position data of a known landmark; a navigation calculation device configured to calculate the position and the heading of the vehicle based on the velocity detected by the velocity detecting device and the yaw rate detected by the yaw rate detecting device; and an estimator configured to estimate, based on a carrier phase and a pseudorange received from a global positioning satellite, (1) an error of the velocity detecting device, (2) an error of the yaw rate detecting device, (3) a position error and a heading error of the vehicle, and (4) an integer-valued bias of a carrier, wherein the estimator is configured to estimate a relative range and/or a relative angle between the known landmark and the vehicle based on the measured angle and the stored position data of the known landmark, wherein the navigation calculation device is configured to update the position and the heading of the vehicle based on the position error and the heading error estimated by the estimator.