M-File Help: EKF | View code for EKF |
Extended Kalman Filter for vehicle pose and map estimation
This class can be used for:run | run the filter |
plot_xy | return/plot the actual path of the vehicle |
plot_P | return/plot the estimate covariance |
plot_map | plot feature points and confidence limits |
plot_ellipse | plot path with covariance ellipses |
display | print the filter state in human readable form |
char | convert the filter state to human readable string |
x_est | estimated state |
P | estimated covariance |
V_est | estimated odometry covariance |
W_est | estimated sensor covariance |
features | map book keeping, maps sensor feature id to filter state |
robot | reference to the robot object |
sensor | reference to the sensor object |
history | vector of structs that hold the detailed information from each time step |
veh = Vehicle(V); veh.add_driver( RandomPath(20, 2) ); ekf = EKF(veh, V_est, P0); ekf.run(N);
veh = Vehicle(V); veh.add_driver( RandomPath(20, 2) ); map = Map(20); sensor = RangeBearingSensor(veh, map, W); ekf = EKF(veh, V_est, P0, sensor, W_est, map); ekf.run(N);
veh = Vehicle(V); veh.add_driver( RandomPath(20, 2) ); sensor = RangeBearingSensor(veh, map, W); ekf = EKF(veh, [], [], sensor, W_est, []); ekf.run(N);
the vehicle state at each time step and the map.% | veh = Vehicle(V); |
veh.add_driver( RandomPath(20, 2) ); map = Map(20); sensor = RangeBearingSensor(veh, map, W); ekf = EKF(veh, V_est, P0, sensor, W, []); ekf.run(N);
Vehicle, RandomPath, RangeBearingSensor, Map, ParticleFilter
EKF object constructor
E = EKF that estimates the state of the vehicle with estimated odometry covariance vest (2x2) and initial covariance (3x3). E = Vehicle, Sensor, RangeBearingSensor, MapConvert EKF object to string
E.EKF object in human-readable form.Display status of EKF object
E.display the state of the EKF.charPlot covariance magnitude
E.plot_P(ls) as above but the optional line style arguments ls are passed to plot. m = E.Plot vehicle covariance as an ellipse
E.plot_ellipse() as above but i=20. E.plot_ellipse.Plot landmarks
E.plot_map() as above but i=20. E.plot_ellipsePlot vehicle position
E.plot_xy(ls) as above but the optional line style arguments ls are passed to plot.Run the EKF
E.run the filter for n time steps.© 1990-2011 Peter Corke.