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20 #ifndef STEERING_FUNCTIONS_HPP
21 #define STEERING_FUNCTIONS_HPP
52 double Sigma[16] = { 0.0 };
55 double Lambda[16] = { 0.0 };
State state
Expected state of the robot.
double covariance[16]
Covariance of the state given by Sigma + Lambda: (x_x x_y x_theta x_kappa y_x y_y y_theta y_kappa the...
Description of a kinematic car's state.
double k1
Weight on longitudinal error.
double sigma
Sharpness (derivative of curvature with respect to arc length) of a segment.
double std_theta
Standard deviation of localization in theta.
double k2
Weight on lateral error.
double theta
Orientation of the robot.
double Sigma[16]
Covariance of the state estimation due to motion and measurement noise.
double kappa
Curvature at position (x,y)
double y
Position in y of the robot.
double kappa
Curvature at the beginning of a segment.
Description of a path segment with its corresponding control inputs.
double alpha3
Variance in lateral direction: alpha3*delta_s*delta_s + alpha4*kappa*kappa.
Parameters of the motion noise model according to the book: Probabilistic Robotics,...
double x
Position in x of the robot.
double delta_s
Signed arc length of a segment.
double Lambda[16]
Covariance of the state estimate due to the absence of measurements.
double k3
Weight on heading error.
double std_y
Standard deviation of localization in y.
Description of a kinematic car's state with covariance.
Parameters of the feedback controller.
double std_x
Standard deviation of localization in x.
double alpha1
Variance in longitudinal direction: alpha1*delta_s*delta_s + alpha2*kappa*kappa
Parameters of the measurement noise.