I want to solve the Sparse Extended Information Filter Slam described by Dr. Sebestian Thrun in Probabilistic Robotics.I stuck in some nested function.
The algorithm is described in page 309 in this book at Table 12.1
Algorithm is like that:
1.Algorithm SEIF_SLAM_known_correspondence($\xi_{t-1}$,$\Omega_{t-1}$,$\mu_{t-1}$,$u_t,z_t,c_t$):
It has four steps:
1.Motion Update
Measurement Update
Update state estimation
Sparsification
Motion Update:
Algorithm SEIF_motion_update($\xi_{t-1},\Omega_{t-1},\mu_{t-1},u_t$)
....... Algorithm body.....
Return $\bar\xi_{t},\bar\Omega_t,\bar\mu_t$
Measurement Update
Algorithm SEIF_measurment_update($\bar\xi_{t},\bar\Omega_t,\bar\mu_t,z_t,c_t$)
Algorithm body.....
Return $\xi_t,\Omega_t$
Now as per algorithm in motion update of SEIF the return value is called in measurement update. I want to know when this type of situation occurred means one function return value is called by a other function Is that call is iterative? If the function body of motion update iterate in a loop then after execution of 1st iteration calling function (measurement update) call this or after full execution of motion update function then measurement update call it?
